B

Current Sensor Capabilities and Future Potential

To clarify the advantages and limitations of individual sensor characteristics, as well as the requirements that these characteristics may place on the performance of a tactical network-centric sensor grid, this appendix discusses each major sensor class in some detail, and it describes current state-of-the-art, likely paths for future growth. To contain the discussion, the sensors participating fully in the grid, that is, those used for surveillance, reconnaissance, and sensor-to-shooter targeting, are emphasized over those dedicated to a single weapon such as a gun control radar. Actually the only major difference between the two types of sensors lies in the relatively short-range and subsecond response requirements of the weapon’s terminal phase, which contrasts with the long-range, seconds-to-minutes response requirements for surveillance, reconnaissance, and targeting. The fundamental technology characteristics are the same for all applications—only the detailed design parameters differ.

B.1 RADAR

Microwave sensors represent the dominant class of air/land battlespace sensors. Inevitably orders of magnitude physically larger than optical sensors with equivalent resolution, microwave radar easily compensates for this size disadvantage with its long-range, all-weather, “imaging” capabilities. As a result, every Navy platform has several radars: for search, navigation, missile fire control, gun fire control, target illumination, and so on.

Although there are still mechanically scanned, microwave tube-powered radars on naval platforms, modern radar implementations, both surface-based and



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities B Current Sensor Capabilities and Future Potential To clarify the advantages and limitations of individual sensor characteristics, as well as the requirements that these characteristics may place on the performance of a tactical network-centric sensor grid, this appendix discusses each major sensor class in some detail, and it describes current state-of-the-art, likely paths for future growth. To contain the discussion, the sensors participating fully in the grid, that is, those used for surveillance, reconnaissance, and sensor-to-shooter targeting, are emphasized over those dedicated to a single weapon such as a gun control radar. Actually the only major difference between the two types of sensors lies in the relatively short-range and subsecond response requirements of the weapon’s terminal phase, which contrasts with the long-range, seconds-to-minutes response requirements for surveillance, reconnaissance, and targeting. The fundamental technology characteristics are the same for all applications—only the detailed design parameters differ. B.1 RADAR Microwave sensors represent the dominant class of air/land battlespace sensors. Inevitably orders of magnitude physically larger than optical sensors with equivalent resolution, microwave radar easily compensates for this size disadvantage with its long-range, all-weather, “imaging” capabilities. As a result, every Navy platform has several radars: for search, navigation, missile fire control, gun fire control, target illumination, and so on. Although there are still mechanically scanned, microwave tube-powered radars on naval platforms, modern radar implementations, both surface-based and

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities airborne, are uniformly configured as electronic-scan, phased-array architectures with all-solid-state microwave power generation. The SPY-1 Aegis radar, the workhorse of the cooperative engagement capability (CEC), represents a pioneering naval implementation of a phased-array radar, albeit with a conventional centralized microwave tube power source. With four fixed-array faces, its electronic scan provides 360° coverage for ship self-defense via search, track, and weapons control. Today, the Navy is considering the development of at least four new radars—the multifunction radar (MFR), an X-band radar for short-range ship defense; the volume search radar (VSR), an L-band radar for medium-range search and cueing to replace the SPS-49; the high-power discriminator (HPD; an X-band radar for ship-based theater missile defense); and a possible future long-range multifunction C/S-band replacement for the current Aegis radar. All are envisioned to be electronic-scan, phased-array architectures with active monolithic microwave integrated circuit (MMIC) solid-state transmitter/receiver (T/R) modules. These surface platform-based sensors are capable of producing “images” of the surrounding air and sea surface space in the traditional radar sense of a georeferenced “map” of the estimated locations of significant observed returns. For an isolated radar, operating in a platform-centric mode, the precision with which the locations of these target reports are defined is of mixed quality—for although a radar usually can provide high-precision range and Doppler measurements, the angular precision is generally poor because of the large radar wavelengths and the dimensions of practically sized radar antennas. Beam widths measured in degrees or finite fractions of degrees are not uncommon. At the range of the target, even for modest ranges of 10 or 20 km, the positional uncertainty perpendicular to the radar beam could be measured in tens to hundreds of meters, whereas the range uncertainty along the beam direction could be less than 1 m. Exploiting the combined measurements of a number of dispersed radars immediately provides a quantum jump in radar-imaging capability without any change in the participating radars’ operational characteristics. Synthetic aperture radar (SAR) accomplishes much the same thing with a single radar sensor, in a different way—by moving it, with a crucial difference in the point of view—looking down rather than up. When an airborne radar is moved along a linear path and appropriate sequential measurements are made from a number of different spatial positions, the accumulated data can be combined in such a way as to duplicate the performance of a virtual antenna equivalent in size to the distance the platform flew during the collection of the data. The resulting radar images of the ground are of “optical quality,” with uniform meter to submeter resolution in all dimensions, and can be obtained over large surface areas, at ranges up to hundreds of kilometers, through almost any kind of weather. SAR sensors are currently available in the battlefield on joint resources such as the Joint Surveillance and Target Attack Radar System (JSTARS) (APY-3), the

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities Box B.1 Hot Topics in Radar Today Digital radar for increased performance, microelectronic compactness, and reduced costs—digital waveform generation, digital receivers, digital true time delay, digital beam forming, and so on Integrated array architectures—bricks versus tile approaches for lower cost per module, for instance, ~$50 per module, from today’s ~$2,000 per module Increased use of real-time synthetic aperture radar (SAR)/ground moving target indicator for ground surveillance and targeting—in-sensor processing enabled by the growth in computer capabilities described by Moore’s law Higher-power T/R modules via wide-bandgap semiconductor technology, e.g., silicon carbide, gallium nitride, and so on Distributed radar similar to the cooperative engagement capability Antistealth capabilities via distributed, bistatic configurations, and, perhaps, low frequencies Ultrahigh-frequency SAR for foliage penetration combining low frequency with very large virtual apertures U-2 platform, and the Global Hawk unmanned aerial vehicle (UAV), with future plans for space platforms (e.g., Discover II). Real-time SAR requires enormous amounts of computational power, from gigaflops to teraflops. In the past, computers with this kind of throughput were large and deployable only on the ground. Early air- or space-based SARs were forced to transmit the raw data to dedicated ground stations for rapid, but not necessarily real-time, availability of the images. Fortunately, computer technology today has advanced to the point where the necessary computational throughput can be provided, in sufficiently small size and weight and low enough costs, to be deployable directly on the UAV or aircraft for real-time SAR. Current thrusts in radar technology are described in Box B.1. B.1.1 Radar Performance B.1.1.1 Resolution Because radar frequencies support large bandwidth signals and long pulse duration, the range measurement capabilities of radar can be quite good—tens of meters to meters or centimeters, if desired. If classification is of interest, hundreds of megahertz of bandwidth might be employed to get a resolution of a few centimeters for automatic target recognition (ATR), whereas in air traffic control (ATC), where only detection and general location of targets are necessary, range resolution might be relaxed to as much as 100 m, leading to a narrow-bandwidth, much cheaper radar. Similarly, ground moving-target indicator (GMTI) radar, using Doppler techniques, can detect radial motion as slow as 1 or 2 km/h.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities In angle, radar beams are typically on the order of a degree or so, which corresponds to antenna dimensions of 60 wavelengths or larger. For X-band (i.e., 10 GHz), a 1° beam width antenna would be 1.8 m across, whereas at L-band (i.e., 1 GHz), it would be 18 m. Of course, bearing estimates are not limited to these dimensions, for with a large enough signal-to-noise ratio, beam-splitting interferometric techniques (e.g., monopulse) can estimate directions to small fractions of the beam width. B.1.1.2 Field of View and Field of Regard Although the generation of multiple simultaneous physical beams from a phased-array radar is possible, operational radars are never operated in this mode, but rather explore their environment one beam at a time. In a conventional, mechanically scanned radar, the beam position is fixed relative to the antenna and thus provides a very restrictive instantaneous field of view (IFOV) equal to the beam width, which for typical radars is measured in fractions of a degree to several or even several tens of degrees. The field of regard (FOR), on the other hand, represents the angular portion of space over which the radar may be pointed by steering the antenna. In a sense, this is a design parameter, and mechanically gimbaled radars, which can rotate a complete 360° in azimuth and tilt up from horizontal to 60° or 70° or even 90° (the zenith), have been built. Phased-array radars, on the other hand, can electronically scan their beams over a wide IFOV, without any mechanical assistance. In practice, deviation angles of up to ± 60°, in any direction off the axis of the array, are readily obtainable, with some compromise in performance at the larger angles because of beam-spreading “squint” effects. All four of the new phased-array radars now under consideration for missile defense will have an IFOV of this magnitude for each single face. For a fixed array, the IFOV and FOR coincide. To expand the FOR of a phased array, two approaches are commonly followed. One simply expands the radar to include individual fixed faces for each azimuthal quadrant and further tips each array face up so that both the horizon and the zenith directions fall within the IFOV capability of the face. This is the approach used by the current Aegis SPY-1 and will no doubt be the design adopted for the future MFR and VSR radars. An alternate approach, which may produce an advantageous cost/performance trade-off in some circumstances, uses a hybrid mechanical-electronic concept. Raytheon’s HPD theater missile defense radar, for example, which is an evolution of the existing theater high-altitude area defense (THAAD) ground-based radar (GBR), has only a single array face. The array is mounted on a gimbaled platform that is mechanically steered to provide IFOV coverage of the full hemispherical FOR. SAR radars address their fields of view and regard in quite a different manner because of the way the raw data are collected. Imagery is generated in a

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities swath parallel to and offset from the flight path of the plane, and the resolution achieved can be varied from high to low by contracting or expanding the width of the swath. Or small, very-high-resolution “snapshots” can be taken anywhere from the minimum to maximum range that the radar can address transverse to the flight path—some SARs support a mode in which the transmitter beam is kept focused on a small region of interest as the plane flies past. The FOR of a SAR depends on the product of the maximum-to-minimum usable range of the sensor and the speed of the plane, whereas the IFOV is highly variable and can vary from low-resolution imagery of the whole swath to a very-high-resolution snapshot of a small portion of the FOR, typically the same number of pixels per second—a trade-off between resolution and search rate. B.1.1.3 Range The range capability of a radar is somewhat of a design parameter, as it varies with implementation parameters such as transmitter power, the microwave wavelength (e.g., S-, C-, X-band), antenna dimensions, detector sensitivity, and the like, as well as the scattering cross section of the intended target set and perhaps some environmental variables. Radars are thus deliberately designed to meet their mission requirements. Surface-based air search radars like the SPS-49 can detect targets 200 to 300 nautical miles away in any direction, and presumably the VSR will be designed with similar specifications. Airborne surveillance radars, such as the APS-145 early warning radar on the Hawkeye E-2C, reach out even farther, to as much as 600 nautical miles, although the JSTAR’s SAR is capable of imaging areas at a range of up to 250 km (~140 nautical miles) transverse to the flight path. B.1.1.4 Geopositioning Accuracy A single traditional radar, whether phased array or not, has poor geolocation capabilities because, although its range measurement uncertainty can be very small if its signal bandwidth is large, e.g., centimeters to a few meters, its angular resolution is always poor in practice because of the limited aperture sizes available; e.g., 0.1° to 1° or 2° beam widths are typical. A 0.1° beam width at 10 km range gives a transverse target location uncertainty of ±8.5 m, which grows to ±85 m at 100 km range. Combining two or more such radars, in a network-centric warfare (NCW) or CEC-like cooperative mode, immediately reduces the combined position location uncertainty to values on the order of the range resolution—degraded by the nonradar problems of determining the individual radar positions accurately via the Global Positioning System (GPS) or some other way. The ultimate limit on geolocational position accuracy is very likely to be dominated by the GPS accuracy of several meters, rather than the inherent capability of the individual radars.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities The geopositional accuracy of SAR sensors is also controlled by the fundamental resolution of the imagery, which can be flexibly varied between broad swaths with tens of meter resolution to small snapshots with submeter resolution, as well as the GPS difficulties of determining the absolute location of the SAR platform at any given time. On the other hand, SAR ground imagery is of such quality that cross-correlation with highly accurate National1 imagery may permit sensor resolution-limited performance to be achieved. B.1.1.5 Area Coverage Rates Search radars—whether mechanically scanned or phased array, ATC, or military—scan the full 360° upper hemisphere out to many hundreds of nautical miles in about 5 to 10 s. If a nominal 450 km range and a 6-s sweep interval, similar to that of the SPS-49, are chosen, the corresponding area coverage rate would be about 105 km2/s—a very high rate of coverage—but the resolution is also quite low. Very typically, a primary search radar is designed to encounter and be able to detect and locate up to several thousand candidate targets during a single full azimuth sweep. Surface-threat, self-defense radars, such as the MFR, try for a faster, approximately 1-s update rate and are horizon-limited to line-of-sight (LOS) ranges of a few tens of kilometers. Assuming a 20 km range and a 1-s sweep, the area coverage rate would be about 1.2 × 103 km2/s—two orders of magnitude less than that of the long-range search radar, but no doubt done with much higher spatial resolution—more pixels per square kilometer. Theater defense radars do not try to search large areas and so have minuscule area coverage rates. These radars are designed to detect, track with high accuracy, and classify incoming threats with their decoys and are cued to small IFOV baskets, within which the targets have been localized by other wide-area coverage sensors. Typically only a few tens of objects are expected to be found in the IFOV. SAR sensors can generate low-resolution images of kilometer-wide swaths at the velocity of the airplane or trade this for a number of high-resolution snapshots using the same number of pixels generated per unit time. JSTARS according to the press is capable of mapping (at unspecified but low resolution, no doubt) 1 million km2 in 8 hours, which translates to an area coverage rate of about 35 km2/s, which is not high when compared with ordinary search radar performance. It is also claimed that the Global Hawk’s SAR will be able to survey, in 1 day, with 1 m resolution, an area equivalent to the state of Illinois (40,000 1   The term “National” refers to those systems, resources, and assets controlled by the United States government, but not limited to the Department of Defense.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities square nautical miles), which translates into a fairly low rate of 1.6 km2/s, a rate compatible with high-resolution imaging. For example, if we hypothesize a platform velocity of 200 m/s and a 10 km swath to be imaged by a SAR at 1 m resolution, all of which sounds quite reasonable, the resulting area coverage rate would be 2 km2/s at a pixel rate of 2 × 106 pixels/s. In contrast to Global Hawk, the Discover II program is targeting a much more capable, spaceborne SAR with a pixel rate of about 20 × 106 pixels/s. B.1.1.6 Communication Data Rate Requirements Building on the information above, it is possible to estimate the communication data rate loads implied by the different classes of radar sensors. Non-SAR radars, as mentioned before, produce highly preprocessed images, with the information data rate heavily reduced through the simple expedient of reporting only “hits”—an elementary form of ATR. If sampling at a particular beam position (i.e., a dwell) finds no candidate target returns of significance, nothing is reported for that “pixel.” A typical report will necessarily consist of a number of digital words describing target location parameters, such as bearing and range, or Kalman filter coefficient updates of information—altogether as many as twenty 32-bit words may be necessary for a worst-case total of 640 bits per report. Thus a search radar, which may encounter as many as 2,000 targets on a single, 6-s, 360° scan, would require a maximum communication bit rate capability of about 200 kbps—although operating ATC radars often see no more than 500 targets at a time and often transfer the reports at 50 kbps over ordinary telephone lines. Horizon search radars, such as the MFR, with their horizon-limited range capabilities, expect to encounter only a few tens to a hundred or so candidate targets to deal with and so, with a 1-s update rate, can expect to need minimal capabilities, similar to the ATC example above—i.e., about 50 kbps. But SAR, the true imaging radar sensor that generates data for every pixel, without exception, will require much higher communication bandwidth capability in order to participate in a network-centric sensor grid—but not nearly as much as is required by a capable modern electro-optical camera, as discussed in the section on electro-optical sensors (Section B.2). Practical SAR sensors produce pixel information at rates comparable to what is implied by the Global Hawk performance capability described above under “Area Coverage Rates” (Section B.1.1.5). Each second, an area of 1.6 km2 is to be sampled at 1 m × 1 m resolution, leading to a pixel rate of 1.6 × 106 pixels/s, which is fairly typical of such systems. Assuming that the location information is implicit in the raster format by which the images are read out, each pixel will need no more than one 16-bit word (or even less) on average for an output reporting data rate of about 25.6 Mbps—which does indeed resemble the requirements of high-quality optical cameras, albeit at the low end of the requirements. Here again, it would be

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities useful to be able to apply some automatic information extraction algorithms via local processing, so that only the compressed, salient information would have to be passed over the network-centric sensor grid communication infrastructure. B.1.1.7 Spectral Issues Different portions of the microwave spectrum are used by different classes of radars, not so much for acquiring additional target-background characteristics for ATR, as is the case with optical sensors, but more often to resolve implementation-application trade-offs. For example, an X-band radar at 10 GHz can achieve the same angular resolution as an L-band radar at 1 GHz with a 10 times smaller antenna. And so X-band is often preferred for high-accuracy applications or for missile seekers where aperture is at a premium. Similarly, the search rate capability of a radar is proportional to the product of the transmitted power and the area of the antenna. In addition, since low-frequency radars need large physical antenna in order to maintain even modest angular resolution and microwave power is much easier to generate at the lower frequencies—e.g., one can obtain T/R modules with hundreds of watts capability at 1 GHz of L-band whereas the current state of the art produces only about 10 W for an equivalent X-band module at 10 GHz and much less than 1 W for frequencies of 35 GHz and beyond—search radars are always L-band or lower. B.1.1.8 Environmental Interactions With few exceptions, radars are “all-weather,” long-range, imaging sensors and for these capabilities they are highly valued. Radar frequencies are, in fact, absorbed and scattered to a minor extent by atmospheric constituents, but not nearly to the extent to which these same obstacles obstruct electro-optical systems. Rain certainly introduces attenuation, but ordinary radars, operating in the 1 to 35 GHz range, suffer very little performance degradation as a result. The effects are the same for fog, dust, and clouds. Only as the frequencies move up into the millimeter range (i.e., 40 to 50 GHz or higher) do serious atmospheric absorption effects appear. Although there is interest in millimeter radars for short-range precision guidance applications, no broad situation awareness roles for them have yet been found, so these limitations are unlikely to have any impact on network-centric operations issues. B.1.1.9 Susceptibility to Countermeasures Clearly radars are susceptible to a variety of countermeasures. Jamming is effective, and all military radars are designed with this possibility in mind. As active sensors, radars inevitably emit radiation, thereby inviting physical attack by missiles like the high-speed antiradiation missile (HARM). For a single radar,

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities operating in a platform-centric mode, often the only protection is to shut down, and the countermeasure has proven effective. On the other hand, with cooperating, distributed radars, as would be characteristic of a network-centric configuration, such a counter may be ineffective as only local portions of the network of sensors need be temporarily shut down, while the rest of the network continues to track the threats. Stealth techniques applied to aircraft have proven effective against many radars. However, very-low-frequency radar, because of size resonance effects, may have certain advantages in the detection of such targets, although perhaps with poor localization capabilities. More interestingly, since a large part of stealth technology depends on the exploitation of geometries that reflect the incident radar waves away from the transmitter, rather than scattering them back, bistatic approaches offer interesting counterstealth possibilities. Radiation scattered away from the transmitting radar may well be receivable by another radar receiver on the battlefield, and this kind of cooperative behavior is just what the network-centric sensor grid concept is going to encourage! B.1.2 Technology Trends and Future Growth in Radar B.1.2.1 Digital Radar One of the most exciting developments in radar today is the vigorous push of digital techniques into many areas that have been traditionally analog (see Box B.1). The idea of a “digital radar” promises increased flexible performance, microelectronic compactness, and reduced costs. Originally radar was based entirely on analog components and techniques—transmitter, antenna, receiver, and signal processing with the results output as analog inputs to a video display. Eventually, analog-to-digital conversion was introduced at the output of the receiver, and digital signal processing has now been a regular feature of high-performance radars for at least several decades. Exploiting the exponential explosion in computer technology, digital signal processing has permitted the continuing introduction of powerful advanced signal processing algorithms (e.g., for space-time adaptive processing) as well as the implemention in real time of complex tasks (e.g., SAR) previously doomed to off-line processing. Other tasks, such as digital beam forming of phased arrays, even at the subarray level, have remained impractical up to the present. But today, as digital clock rates move into the gigahertz range and computational capabilities grow from gigaflops to teraflops, digital beam forming, particularly at the subarray level, now appears feasible. The term “digital radar,” however, suggests much more than signal processing and beam forming. It now is possible to consider replacing many of the remaining analog radar components with much more compact, lower-cost digital equivalents—e.g., receivers, waveform generators, and so on. The idea is to move the analog-to-digital converter (ADC) away from the signal processor and as close to the front end of the radar

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities as possible—in the extreme, an ADC at every T/R element in the phased array. The transmit waveform would be generated digitally and the signal transported in digital form over fiber-optic data lines to the individual T/R modules where it is digitally delayed to achieve true time-delay phase shifting, passed through a digital-to-analog converter, amplified by the solid-state T/R module, and transmitted. After some filtering and low-noise amplification, the received signal would be digitized directly at the microwave frequency or after a single stage of down conversion, digitally delayed as appropriate, and sent via fiber optics to the digital signal processor where pulse compression, beam forming, space-time adaptive processing (STAP), and so on will be carried out at real-time speeds. Figure B.1 illustrates the performance of current state-of-the-art ADCs. To date, all available ADCs fall more or less below the diagonal line, which represents a form of jitter limitation. Successful implementation of digital radar concepts requires performance above the jitter-limit line. Currently the Defense Advanced Research Projects Agency (DARPA) and others are investing heavily FIGURE B.1 State-of-the-art analog-to-digital converter (ADC) performance with current ΔΣ “breakthrough” targets indicated. SNR, signal-to-noise ratio. © Copyright 2000 Raytheon Company. All rights reserved. Reprinted with permission.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities in finding ways to circumvent this apparent technology limit through the exploration of very-high-speed, so-called delta-sigma (ΔΣ) 1-bit sampling techniques, which are common and successful in high-fidelity audio today at much lower sampling frequencies. A few more bits above the line will make digital radar a reality. The increases in performance and decreases in size and weight can be enormous—one study indicated over a 100-fold decrease in the volume of the receiver hardware by going from analog to digital. Key to reaching these goals is the development of high-bit, gigahertz sample rate ADCs that are compact, low power, and inexpensive. DARPA, the Office of Naval Research (ONR), and others are currently supporting major thrusts in this much-needed ADC technology, and one can expect to find radars with digital receivers, and perhaps digital beam forming and digital true-time delay, deployed within the next 5 years. Many radars today already employ digital waveform generation. B.1.2.2 Array Architectures—Low-cost Transmitter/Receiver Modules Phased arrays are expensive. If the total cost of the antenna structure is divided by the number of elements (i.e., T/R modules) in the antenna, costs of $1,000 to $2,000 per element are the norm. With 10,000 to 20,000 elements in a typical high-performance radar, such as MFR or HPD, the antenna alone can cost tens of millions of dollars. The fundamental building block of a phased-array radar—the T/R module—is a complex device containing multiple GaAs integrated microwave circuits (e.g., MMIC amplifiers, phase shifters, and so on), digital circuits (e.g., controllers), microwave, digital and power interconnects, radiating elements, mechanical support and cooling structures, and so on. For performance reasons, this module must be packaged to fit into an area on the face of the antenna of only one-half wavelength by one-half wavelength—at X-band, this is only 1.5 cm in each dimension. The development of MMIC technology over the past several decades has greatly reduced the costs for these chip components, through the adoption and extension of techniques from silicon integrated circuit manufacturing. Most of the remaining costs lie in the packaging, interconnects, assembly, and testing, and these aspects can be minimized by the use of highly integrated modular array architectures. So-called brick architectures, which are common today, meet the packaging challenge by building back along the third dimension away from the face of the array. Generally a modular structure is created with 4, 8, or 16 T/R modules built into a single integrated unit with integral power supplies and cooling. Costs for these highly integrated designs are now dropping to about $500 per element. An alternate architecture, the tile array, attempts to meet the wavelength constraints by building directly in the plane of the antenna with unpackaged

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities or an artifact to be a genuine target. Since optical sensors observe only the exterior aspects of objects, appearances are everything. Jamming, in the form of a bright flare or a directed laser beam in the FOV of the sensor, can be a serious threat because optical sensors are frequently operated “wide open” in an effort to optimize sensitivity by maximizing the number of photons collected. The collected optical flux from a directed laser beam (e.g., from a tactical high-energy laser weapon, such as that currently under development jointly with Israel), operating within the IFOV of an imaging sensor, will be focused by the sensor’s collection optics more or less onto a single detector in the focal plane. Under these circumstances, even modest high-energy laser power levels can physically destroy detector elements. Moreover, both the flare and the laser weapon beam, even if actual destruction does not result, can, by diffraction, cause large numbers of the detector elements around its image in the focal plane to saturate, thereby temporarily blinding large portions of the IFOV. B.2.2 Technology Trends and Future Growth in Electro-optics B.2.2.1 Uncooled IR Focal Plane Arrays One of the most exciting advances in electro-optics in recent years has been the migration of microelectromechanical systems (MEMS) technology into IR focal planes. Arrays of tiny thermally sensitive structures (bolometers, as it were) can be fabricated on a silicon wafer using slightly modified integrated circuit manufacturing techniques, and along with each, an integrated on-wafer electrical measurement circuit to determine the instantaneous temperature of the microbolometric element. When an IR image is projected onto this wafer array by an optical system, the element-by-element temperature pattern that results from the local heating caused by the light is read out of the wafer as electrical signals and the device acts as an IR FPA, but with one enormous advantage over a traditional semiconductor FPA—it does not need to be cooled. Such MEMS-based FPAs operate at room temperature, with almost the same sensitivities (i.e., minimum detectable temperature differences measured in tens of millikelvins) as the liquid nitrogen-cooled semiconductors FPAs. Figure B.2 shows an inexpensive, compact, uncooled IR camera with a closeup of its MEMS focal plane and an image demonstrating a temperature sensitivity of 27 mK, comparable to the performance of a cooled IR FPA. Add to the temperature advantage the facts that, as a close relative of a silicon integrated circuit, these uncooled FPAs are inexpensive to manufacture, are physically compact, and require very little power. For these very good reasons, uncooled IR cameras are going to find wide usage on the battlefield—as surveillance and terminal guidance sensors. In particular, they are perfect for all classes of unmanned air vehicles, including mini- or micro-, one-use, throw-away UAVs.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities FIGURE B.2 Microelectromechanical systems-based uncooled infrared camera and temperature-sensitive image. Their one apparent disadvantage is that the time response of an uncooled FPA is limited by thermal inertia to update rates of 30 Hz or below, whereas traditional semiconductor FPAs can operate at update rates as high as 400 Hz. For surveillance, this slow update rate is not a problem, but for terminal guidance, because of the high closing velocities and possibly rapid scene dynamics, this slow rate could be restrictive. B.2.2.2 Advanced Focal Plane Arrays Traditional FPAs continue to grow larger with 512 × 512 pixel HgCdTe arrays already deployed and 106 pixel arrays in sight. In addition to having more pixels, the FPAs are getting “smarter” with increasing amounts of on-chip sampled analog preprocessing being added. B.2.2.3 Special-Purpose Focal Plane Arrays Over the past decade, a number of interesting special-purpose multispectral FPAs have been developed. Both hybrid and monolithic techniques have been

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities used to create stacked, dual-band, focal planes that produce simultaneous images in two different portions of the spectrum, say a 3 to 5 mm band and an 8 to 14 mm band, and both are perfectly pixel-aligned. This provides an ideal input to a sophisticated multifrequency ATR algorithm for target detection and classification. Recently this pixel-aligned concept has been successfully applied to image polarization. That is, the FPA generates simultaneous, pixel-aligned images of the scene in each of two orthogonal polarizations. In all other respects, it acts like any other traditional FPA with respect to sensitivity, update rate, and so on. Since manmade objects tend to retain polarization and natural background objects generally depolarize, this special sensor offers interesting potential for target discrimination. All these possibilities are currently being explored. B.2.2.4 Ladar Three-dimensional Imaging The ability of laser imaging systems to obtain high-resolution, range-to-target measurements offers enormous advantages for target recognition. The sensor directly measures the geometric features of the object of interest and is not confused by scene illumination effects and the unknown distances, which trouble classical passive IR or visible-image ATR algorithms. The height of the tank or truck, or its precise orientation toward the sensor, can be directly measured without guesswork. These advantages have been understood for decades; however, the lasers available have generally been bulky and expensive and no such system has yet been deployed, although the expected performance advantages have been demonstrated in the field with brassboard prototypes. Recently, a new generation of compact diode-pumped solid-state laser sources (e.g., Lincoln Laboratory’s “microchip” YAG lasers) has evolved and interest in this promising technology has reawakened. It seems to offer unique potential for terminal guidance with automatic target selection and aimpoint determination based on geometric information about the target. Given the potential sensitivity of long-range, land attack, precision weapons to GPS jamming, such capable terminal sensors ought to be of great interest. B.2.2.5 Hyperspectral Imaging Multispectral imaging, with only two or three selected bands, has proven effective in enhancing the ability to detect and classify some targets. However, external appearances can often easily be altered and controlled by simple techniques (e.g., camouflage). It seems obvious that if detailed spectral information could be collected about every scene pixel, it might be possible to detect the difference between target and background pixels, particularly if it were known just which portions of the spectrum contained these crucial differences. For

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities example, the green dyes used in the World Wars to camouflage soldiers hidden among the trees, while matching the green of the trees, had a completely different spectral response in the red—the red of autumn leaves is always present, just masked by the overwhelming chlorophyll green most of the year—and were easily detected by looking through a red filter. Following this train of thought, so-called hyperspectral imaging sensors have been built with information collected at each image pixel, over tens to hundreds of individual spectral bands—some only a few nanometers wide. The inevitable result is a classic case of data overload with no chance at all for real-time response—at least, that is, until computer technology catches up. Given the pluses and minuses, it is not clear how valuable hyperspectral imaging will prove in the battlefield. Application to high-dynamic sensor/shooter/weapons scenarios seem unlikely, but longer-latency situational awareness might be considerably enhanced if the needed algorithms can be developed. B.2.2.6 Optical Phased Arrays Considering the performance advantages phased-array electronic beam steering has given to radar such that it completely dominates modern high-performance radar today, it is not surprising that considerable effort has been expended seeking ways to extend electronic beam agility to electro-optics. Given the minuscule dimensions of the wavelengths of light and the requirement to separate adjacent phase shifters by half-wavelength intervals in order to avoid grating lobes, it is easy to see that the challenge is formidable. Clearly an optical beam steering array cannot be implemented by assembling discrete elements as with a brick architecture radar phased array. Monolithic techniques, resembling those of the tile architectures, are called for. Based on liquid crystal phase-shifting materials, which are optically transparent with electric field variable indices of refraction, combined with photolithographically deposited transparent electrode patterns, optical phased arrays have been developed and demonstrated in the past few years. Limited by current technology to small deflection angles of only a few degrees and to switching rates below 1 kHz, optical phased array technology is nevertheless impressive and promising. DARPA is now in the process of establishing a well-funded program to extend the angular capabilities of optical phased arrays to angles as large as ± 90°. B.3 SONAR Acoustics—the propagation of sound waves through air, water, or solid ground—provides another remote sensing capability of crucial importance to the Navy because acoustic sonar permits us to “see” long distances underwater where many threats hide, but where optical sensors work poorly and radars, not at all.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities As a wave phenomenon, sonar shares with radar and EO many of the same equations determining system performance, e.g., the relationship between aperture size and wavelength to beam width and angular resolution or between signal bandwidth and measurement accuracy. Thus, from a system point of view, sonar is a familiar relative of radar and EO and can perform all the same functions—detection, classification, and localization of underwater and sea-surface targets, with the generation of situation awareness “images” of portions of the sea. On the other hand, the medium that sonar systems have to deal with is absolutely terrible. Underwater sound propagation is almost never in a straight line because of strong medium nonuniformities associated with time and spatial variations in temperature and salinity. Reflections from the sea surface and bottom are common. And the sea is never free of acoustic noise of all kinds—from waves, from manmade objects like ships, and from biological sources like whales, porpoises, and fish. The velocity of sound in water is very low—roughly 1 mile/s—which seriously increases the time needed to collect information for active sonar detection, classification, and localization of distant targets. Finally, the absorption of sound in water is a strong, increasing function of the acoustic frequency—low frequencies (e.g., ≤ 3 kHz) are needed for long range but cannot achieve high angular resolution because of the very large antenna sizes required and the unpredictable spatial variations in sound propagation. And although high angular resolution is possible at high frequencies (e.g., 35 to 350 kHz), it can be achieved only at fairly short ranges of several hundred meters or less. The result of these media-induced obstacles is that sonar performance in general is very slow, with image resolution and target location capabilities that degrade rapidly with range. Because of their importance, and in spite of their many limitations as sensors, naval sonars are nevertheless ubiquitous throughout the battle group, since the underwater threats are many and real. Every ship or submarine has several—hull mounted or towed; active or passive; high frequency, medium frequency, or low frequency; and so on. And the battlespace usually contains a number of unmanned sonars—some permanently moored, e.g., strategic arrays; others temporarily drifting, e.g., sonobuoys; and others self-propelled, e.g., unmanned underwater vehicles (UUVs) or remotely operated vehicles (ROVs). It is thus natural to consider increasing the fleet’s antisubmarine warfare (ASW) capabilities by shifting from a platform-centric to a network-centric point of view. With the right communications, a widely dispersed set of sonar sensors can be made to emulate CEC and act as a single sonar system that, like the CEC radar, would be thought of as organic to a fleet of ships rather than to any individual platform. Since sonar, in contrast to radar, makes extensive use of passive detection, it is also natural to expect a mixture of passive and active modes throughout the network producing an even larger synergistic effect than would be obtained by operating all the sensors in the same mode. Clearly CEC

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities Box B.3 Hot Topics in Sonar Synthetic aperture sonar Proliferation of cooperating unattended underwater vehicle platforms Autonomous distributed systems—moored and drifting arrays Ultra-broadband sonar—biologically inspired should consider extending its operation to a mix of active and passive (i.e., bistatic) operations because of the antistealth and counter-countermeasure (CCM) advantages. Current thrusts in sonar technology are described in Box B.3. B.3.1 Sonar Performance B.3.1.1 Resolution Direct measurements of range can only be obtained from an active sonar, and the resolution is determined fundamentally, as is the case for active RF systems, by the time-bandwidth product of the transmitted signal and the signal-to-noise ratio. Because of the low operating frequencies characteristic of acoustics, time-bandwidth products (and hence pulse compression ratios) of sonar signals are typically on the order of 100 or so, whereas for radar, products of thousands to tens of thousands are common. Although a wide range of range resolution performance is available by varying the amounts of pulse compression applied, active sonar resolution typically is controlled to match the size of the target sought in order to maximize the signal-to-noise ratio and hence the detectability of the return pulse. Too high a resolution causes the sonar to “see” only pieces of the target at a time and reduces the return signal maximum amplitude. Angular resolution achievable by a sonar is determined largely by the diffraction properties of the antenna and again the signal-to-noise ratio. But the beam width alone is not the limit as fractional beam width accuracy is certainly possible through interferometric techniques or what is called in radar “monopulse.” Because of the relatively large wavelengths associated with acoustic radiation, the phased arrays used for sonar typically do not have more than a few tens of elements (e.g., 10 to 40) along any direction, whatever the frequency range employed. Hull-mounted sonar, for example, such as the BQQ-5 submarine sonar, has a 15 ft diameter spherical array, whereas the SQS-53 sonar for large surface ships has a 16 ft cylindrical array and the SQS-56 surface ship

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities sonar, only a 4 ft diameter. At a frequency of 3.5 kHz, these dimensions lead to beam widths of 3° to 10°. For high-frequency (500 kHz) imaging sonar, the antenna dimension need be only 64 cm long to obtain a 3° beam width, whereas a long-range search system emitting at 1 kHz would have to be 500 times longer (e.g., 320 m) to have the same beam width. B.3.1.2 Field of View and Field of Regard As phased arrays, all sonar antennas can be readily steered over large fields of regard. Linear arrays, hull mounted or towed, can achieve ± 60° or more, whereas some hull-mounted arrays are circular and can be steered through a full 360°. Long-range sonar exploits this capability by creating a few tens of beam positions at different angles so that the full FOR can be monitored simultaneously, each individual beam being a few degrees (e.g., 3° to 30°) in width, depending on the size of the array and the operating frequency. Side-scan imaging sonar generally is restricted to producing a narrow horizontal beam (e.g., 1° to as small as 1/5°) with a much broader beam in the vertical (e.g., 40°) and thus has a very small IFOV that is scanned forward by the motion of the platform. The IFOV for surveying can be as large as 15 knots or for classification (of mines, for example), as slow as 1 to 5 knots. Projected on the bottom, the IFOV of a side-scan sonar may be no larger than 30 m2, e.g., a strip 1/5 m by 150 m. B.3.1.3 Range The effective range of a sonar is a strong function of the frequency used due to the quadratic increase in water absorption of sound with increasing frequency. Sonar utilizing low frequencies of 3 kHz or less can often detect targets up to 100,000 yd (~50 nautical miles) or more. But because of the unpredictable properties of ocean propagation, with possibilities for refraction down until a reflection off the sea bottom occurs (i.e., bottom bounce) or refraction down followed by refraction back up to the surface (i.e., convergence), it is very difficult to determine exactly how far away the acoustic source or reflection is. In the so-called convergence zones, detection can be excellent, even though the ranges are large. However, these zones can be quite narrow (~1 percent of the range); and between the zones, which can repeat at intervals of 40,000 to 80,000 yd, depending on which of the world’s oceans the sonar is operating in, nothing much can be detected. The bending effects of the ocean gradients result in “blind” regions between convergence zones, within which targets cannot be detected by the sonar—that is, volumes of water that cannot be reached by acoustic beams radiated by the sonar because they are refracted away from and around these regions. Passive sonar, of course, cannot directly determine range at all—only azi-

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities muth or bearing to the target can be estimated. Because of the slow dynamics of vehicle motion in the ocean, it is a common practice for the sonar, after receiving a contact on a certain bearing, to have the ship turn and take a run to a different location and then use the bearing estimate from the new location to triangulate with the earlier bearing to obtain a rough location of the acoustic source. Several cooperative passive sonars, viewing the same target simultaneously from sufficiently separated physical locations in a network-centric sensor grid, could, of course, provide instantaneous, more accurate localization. B.3.1.4 Imaging for Mine Location Side-scan sonar operating at high frequencies (e.g., 100 to 500 kHz) can produce good images of mines for detection and classification, with resolutions on the bottom 10 to 30 cm. However, because of absorption, such performance is limited to ranges from the platform of only 100 to 200 m—a distance that can lie within the lethal range of the mines. Often a compromise is chosen, searching first at a medium frequency (e.g., 35 to 100 kHz) which allows a reasonable standoff distance and good detection possibilities, followed by a slow-speed, closer-range, high-frequency imaging pass for classification or even the use of an ROV or swimmer. Anyway it is done, it takes an enormous amount of time. Exploitation of the two-dimensional acoustic shadows of the mines have been used successfully to produce effective ATR algorithms for mine classification. B.3.1.5 Geopositioning Accuracy Except at mine-detecting ranges (i.e., within a few hundred meters of the platform), the ability of sonar to determine a target’s position in range and azimuth is extremely poor. With degrees of beam width, unknown paths of propagation, and great range uncertainty, sonar is of little use for geolocation. Unfortunately, for underwater targets, sometimes that is all that can be done. B.3.1.6 Area Coverage Rate Active sonar for medium or long range is limited by the long round-trip return time of the transmitted energy—for a range of 20 nautical miles, the round-trip time is about 23 sec. If the sonar explores the 20 nautical miles radius ± 60° FOR permitted by the phased array by 30 different 4° beams, the area coverage rate is only about 2 km2/s. This should be compared with an above-the-surface surveillance radar that can cover a 200 nautical miles range by 120° segment in only 4 s for an area coverage rate of 36,000 km2/s. On the imaging side, route surveying for mines with a side-scan sonar in the push-broom mode with 2000 m wide swath and moving at 15 knots has an area

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities coverage rate of only 1/65 km2/s. And a mine-classification high-frequency sonar, covering a swath of 150 m at a speed of 5 knots, has an even smaller area coverage rate of only about 400 m2/s, which is a minuscule 1/2500 km2/s or only 1.44 km2/h. Finding something in or on the bottom of the ocean can take a very long time, and because of physics, our accelerating technology has not yet been able to overcome the obstacles. B.3.1.7 Communication Data Rate Requirements In spite of the large amounts of computational resources and time that have to be expended in order to extract meaningful information from active or passive sonar signals, the resulting data are so sparse (i.e., not many target-like objects within range at any given time) and are collected so slowly and with such low resolution that the resulting data rates to transfer one sensor’s data to another location put no strain at all on an RF communication link. For example, a medium- or long-range surveillance system might need to transfer a video screen-worth of data (say, 400,000 pixels at 8 bits) every 5 or 10 s, resulting in a data rate no larger than 650 kbps. Even a high-resolution mine-hunting side-scan sonar, producing a 20 cm pixel over a 150 m swath on the bottom and moving forward at 5 knots (i.e., ~2.6 m/s) results in only about 10,000 pixels/s (say, 10 bits each) for a total rate of only 100 kbps. On the other hand, if we wished to employ an acoustic communication link, say, between cooperating UUV platforms, the necessary data rates could stress the system, and further local processing with ATR-like algorithms and perhaps the application of data compression techniques would be called for. B.3.1.8 Environmental Issues The effects of the low acoustic propagation velocity, the media variability and inhomogeneity, and the frequency-dependent absorption that seriously limit sonar performance in the open ocean have been discussed. Operation in the littoral, because of the shallow depths and coastal waves, greatly aggravates an already difficult sensor problem because of the more frequent reflections from the top and bottom surfaces of the water, the absorption in and irregularity of the bottom, and the high levels of wave and surface noise characteristic of this environment. Sonar designed for the open ocean does not work well, if at all, in the littorals. New designs that properly account for the physical characteristics of the littoral need to be developed, although it is far from clear that major breakthroughs in single-sensor performance are possible. More likely the problem requires a distributed solution with large numbers of short-range sensors acting cooperatively in a network-centric mode.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities B.3.2 Technology Trends and Future Growth in Sonar B.3.2.1 Synthetic Aperture Sonar The technology of conventional side-scan sonar for the imaging of mines has saturated, as it were, in that the range capabilities and the area coverage rate of several nautical square miles per hour are strongly limited by the acoustic velocity and attenuation properties of sea water—not by technology per se. The 10 to 20 cm resolution obtainable from practical antennas is considered more or less adequate for mine detection and classification. It is in this context that interest in synthetic aperture sonar (SAS) has been reawakened in the past several years, with the hope that the imaging resolution and range (and hence area coverage rate) might be increased through the use of low-frequency acoustic signals and very large virtual antennas, without giving up the 10 to 20 cm resolution. Based on the very same principles as microwave SAR, the possibility for SAS was suggested early, 30 to 40 years ago. Nevertheless, very little real progress has been achieved in the intervening decades, for the same physical obstacles (e.g., media inhomogeneity, extreme temporal variability, and the slow 1 mile/sec acoustic propagation velocity) that afflict all sonar applications present even larger challenges for the coherently processed SAS. For example, the precise position of the sonar transmit-and-receive components must be known over the whole length of the virtual antenna, to fractions of the acoustic wavelength—e.g., to millimeters if a relatively low mine-hunting frequency of 100 kHz is used where λ = 1.6 cm. Because of the difficulties in achieving this positional knowledge, autofocus algorithms have been evoked which work to some extent but are so computationally expensive that they cannot yet be carried out in real time. Nor is it clear, because of media temporal fluctuations, that signal coherence can be maintained over the time it takes to traverse the full virtual antenna. Nevertheless, interest in SAS is high at the moment, but it is fair to say that it is still “in its infancy” today. Because of the difficulties in the physics, not very much has yet been demonstrated except under closely controlled conditions. B.3.2.2 Cooperating Unmanned Underwater Vehicles In the spirit of network-centric operations, concepts are being actively explored for mine hunting involving multiple UUVs working in parallel. Equipped with very-high-frequency, 1 MHz or higher, side-scan imaging sensors and, perhaps in the future, high-resolution laser optical imaging systems, with ranges of only a few tens of meters at best, these mobile underwater sensors are perfect candidates for cooperative networking. Although these sensors operate independently at the moment, future cooperation through surface RF or underwater acoustic communication links, leading to a distributed and adaptive metasensor concept, should produce the synergistic multiplication of capabilities and effectiveness expected from networked concepts.

OCR for page 352
Network-Centric Naval Forces: A Transition Strategy for Enhancing Operational Capabilities B.3.2.3 Autonomous Distributed Systems Distributed arrays of acoustic sensors with elements less capable than the mobile UUVs suggested above are also of great interest for littoral or shallow water (100 to 500 m) area surveillance. Deployed like sonobuoys and drifting or moored in place, each node is envisioned to possess considerable on-board signal and data-processing resources and to be capable of passive automatic detection and classification as well as active signal processing. These individual capabilities, complemented by the networked acoustic/RF communications, would permit them to operate as a single large and very capable coherent distributed sonar. A typical multistatic configuration might consist of a few active sources and as many as 10 to 100 “smart” sonobuoy-like nodes distributed broadly over the area under surveillance. In addition to the loosely coupled multistatic systems of active sources and smart sonobuoys, various physically connected drifting or moored arrays are under consideration. The autonomous drifting line array would consist of a very-low-frequency passive array of up to 100 hydrophone elements, drifting freely in the ocean currents. Data from the linear, but almost certainly not straight, aperture would be processed on board the array through battery-powered computer resources and would report detection/classification information back to the decision makers via an RF link as necessary. Other concepts envision similar autonomous arrays moored in shallower water. Key to the success of all these concepts is the availability of significant local on-board sensor processing supported by long-life batteries. B.3.2.4 Ultra-Wideband Sonar In spite of our technology, animal sonar, as utilized by bats and porpoises, far exceeds our capabilities for precise location and target classification. Operating in complicated environments, in the presence of perhaps dozens of competing individuals, these animals emit complex, very broadband sonar pulses that they change rapidly as they move from detection to classification and final capture of prey, apparently adapting their internal signal-matched filter on a pulse-to-pulse basis, easily sorting out their own signals from those of other bats or porpoises. Since the early 1990s, building on pioneering university studies of bat sonar, the Navy has sponsored efforts to develop a biologically inspired, ultra-wideband sonar, using multioctave signals and multichannel nonlinear processing with coherent recombination. Computer studies applying such processing to existing narrowband field data have already demonstrated an encouraging reduction in false alarms. The development of transducers capable of emitting the desired ultra-wideband signal is under way, and it is hoped that soon we will be able to duplicate in the littorals at least some of the extraordinary capabilities common in nature.