GLRT subspace detection for range and Doppler distributed targets

Abstract

A generalized likelihood ratio test (GLRT) is derived for adaptive detection of range and Doppler-distributed targets. The clutter is modeled as a spherically invariant random process (SIRP) and its texture component is range dependent (heterogeneous clutter). We suppose here that the speckle component covariance matrix is known or estimated thanks to a secondary data set. Thus, unknown parameters to be estimated are local texture values, the complex amplitudes and Doppler frequencies of all scattering centers. To do so, we use superresolution methods. The proposed detector assumes a priori knowledge on the spatial distribution of the target and has the precious property of having a constant false alarm rate (CFAR) with the assumption of a known speckle covariance matrix or by the use of frequency agility.

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

“…The model (4) is suitable for the cases that the range resolution is not too high, target is low-speed and steady flight, and the integration interval is not too long. When target rotation can't be neglected and some range cells probably contain a few strong scatterers but target has not range walking across cells during integration, the 2D scattering center model has to be employed and target return vectors are as follows [10]:…”

“…The estimate precision depends on the ratio K/N and the estimatê R tends toward the actual covariance matrix R as the ratio K/N tends toward infinite [10]. In term of the estimateR, the temporal whitening filtering is row-wise realized by:…”

“…] is a Ndimensional zero-mean complex Gaussian random vector with the covariance matrix R whose diagonal entries are one and the positive random constant χ follows the Gamma distribution [10]:…”

“…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.…”

“…The target return model available in [6][7][8][9] is unsuitable for range-spread targets in high-speed manoeuvring flight, whose complex HRRPs exhibit much more complicated change. The return model with both range and Doppler spreads can describe targets with rotation but without range walking across cells during integration [10][11][12]. Under this model, the GLRT-based detectors suffer from additional performance loss, because the rotation incurs different Doppler shifts in the individual cells and too many model parameters need to be estimated from the received data corrupted by strong clutter.…”