Spatial Statistics and Digital Image Analysis (1991) / Chapter Skim
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8. Spatial Signal-Processing in Radars and Sonars
8. Spatial Signal-Processing in Radars and Sonars
Pages 147-158
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A planar array is used for sonar to detect seismic explosions ant! for radar to track distant flying objects, and a linear array is used for sonar to detect distant underwater objects.
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acoustic data recorded at the josh sensor at time t, Aft) is the acoustic signal received at the Ah sensor at time t, dwj~t)
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frequency such that AT ~ 2;r, Tj = (; 1~4 cos ’/c = the time delay of the signal planewave arrival at the Josh sensor relative to the first, = the distance between two adjacent sensors,
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~ (~3~4) Then, in the absence of the interference z, the logarithm of the likelihood ratio becomes log,dpl~r)
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Of course, such an adjustment must be done rapidly so that accurate signal detection and direction-of-arrival estimation can be accomplished. The iterative methods of adjusting and their convergence characteristics have been extensively studied.
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., M . We allow some As to be zero since not all frequency components have all M arrival directions.
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Although the linear array (with or without the equal spacing) is the most common configuration, due primarily to the ease of implementation, the sampling pattern can be considered as a factor with respect to which the detection and estimation performance can be optimized.
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The ESPRIT (Estimation of Signal Parameters by Rotational Invariance Techniques) method (Roy and Kailath, 1989)
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~~ ~~ I ~ ~~ +~ +~ ~~ ~^ ~1~^ the ~/~ ~ I S.5 Future Research Considerations The assumption that both the signal and the interference plus noise be Gaussian fields is primarily for mathematical convenience since the problem then is completely treatable by linear operators in Hilbert spaces, and Gaussian fields are the simplest class of the second-order random fields. However, there are evidences, especially in the case of the ocean acoustics, that the probability distributions of the interference fields considerably deviate from the Gaussian distribution (Middleton, 1987~.
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Porat, Performance analysis of a nub steering algorithm based on direction-of-arrival estimation, IEEE Trans. Acoust., Speech, Signal Process.
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[10] Middleton, D., Channel modeling and threshold signal processing in underwater acoustics: An analytical overview, [EKE ]
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