Spatially distributed target detection in non-Gaussian clutter

Abstract

Two detection schemes for the detection of a spatially distributed, Doppler-shifted target in non-Gaussian clutter are developed. The non-Gaussian clutter is modeled as a spherically invariant random vector (SIRV) distribution. For the first detector, called the non-scatterer density dependent generalized likelihood ratio test (NSDD-GLRT), the detector takes the form of a sum of logarithms of identical functions of data from each individual range cell. It is shown under the clutter only hypothesis, that the detection statistic has the chi-square distribution so that the detector threshold is easily calculated for a given probability of false alarm P F. The detection probability P D is shown to be only a function of the signal-to-clutter power ratio (S=C) opt of the matched filter, the number of pulses N, the number of target range resolution cells J, the spikiness of the clutter determined by a parameter of an assumed underlying mixing distribution, and P F. For representative examples, it is shown that as N, J, or the clutter spikiness increases, detection performance improves. A second detector is developed which incorporates a priori knowledge of the spatial scatterer density. This detector is called the scatterer density dependent GLRT (SDD-GLRT) and is shown for a representative case to improve significantly the detection performance of a sparsely distributed target relative to the performance of the NSDD-GLRT and to be robust for a moderate mismatch of the expected number of scatterers. For both the NSDD-GLRT and SDD-GLRT, the detectors have the constant false-alarm rate (CFAR) property that P F is independent of the underlying mixing distribution of the clutter, the clutter covariance matrix, and the steering vector of the desired signal.

Detection of Range Migrating Targets in Compound-Gaussian Clutter

“…On the contrary, this phenomenon does not exist for non-migrating targets, where the detection performance in spectrally white clutter (or noise) does not depend on the velocity of the target. This effect is similar to performance improvement of an extended target compared to a point target [9], [14]. The major difference between the two models is that for range migrating target, its signature is summed up coherently along the range walk, while the responses of a range extended target are integrated incoherently along range.…”

“…If ν → ∞, then the clutter tends to Gaussian distribution with power p τ (τ ) = δ (τ − µ), where µ is the known mean power of clutter. By definition (14), the non-linear memoryless function…”

“…Moreover, due to the absence of range-walk, the scatterers are assumed to be present in the same range cells during the whole CPI, as shown in Figure 1, c. The decision rule then becomes a combination of the statistics (7) estimated from the range cells on the target [11], [14].…”

“…Also some studies investigate the detection of range-extended targets in compound-Gaussian clutter, e.g. [9], [14]. A comprehensive overview of detection structures for modern radars can be found in [11].…”

Entropy-based detection of manoeuvring range-spread targets in homogeneous weather clutter

“…Compared with those detectors in white Gaussian noise, detecting range-spread targets in nonstationary clutter environments is more complicated and has recently received much more attentions [6][7][8][9][10][11][12][13][14][15]. Those methods mainly focus upon steady range-spread targets, such as air targets in steady flight or slow ship target in sea clutter.…”