i Abstract This thesis investigates the problem of target parameter estimation and performance analysis of multiple-input multiple-output (MIMO) radar in the presence of non-Gaussian clutter. During the past decades, multiple-input multiple-output (MIMO) radar has become a research subject of growing interest, due to its superior performance in many aspects over the traditional phased-array rad...

Traditional space-time (ST) adaptive processing (STAP) theory is based on the assumption of narrowband or “zero-bandwidth,” where decorrelation within ST snapshot ignored. However, with radar bandwidths increasing, this becomes invalid due to deteriorated received signals snapshot. The directly causes dispersion in both spatial and temporal domains, leading spreading clutter spect...

This tutorial provides an introduction to the application of knowledge-based processing to the general radar problem. We interpret knowledge-based processing as the use of adaptivity and the exploitation of prior knowledge in such a way as to choose the optimum processing method in each case, and we interpret the general radar problem as the detection, classification and tracking of targets aga...

We propose a new class of Subspace filter based algorithms for detecting targets in forest clutter environment. The training phase of the proposed SAR target detection algorithms “learns” the clutter characteristics using local or global clutter subspaces. Both off-line and on-the-fly self-training versions of the algorithm are presented. These adaptive approaches utilize the Singular Value Dec...

Sea clutter refers to the radar returns from a patch of ocean surface. Accurate modeling of sea clutter and robust detection of low observable targets within sea clutter are important problems in remote sensing and radar signal processing applications. Due to lack of fundamental understanding of the nature of sea clutter, however, no simple and effective methods for detecting targets within sea...

This report evaluates the capability of Airport Surveillance Radars (ASRs) for the detection of low altitude wind shear associated with the outflows of dry microbursts. It describes results of simulations of dry microburst observations by an ASR. These simulations incorporated weather and clutter data collected by the FL-2 pencil-beam Doppler weather radar at Denver Stapleton Airport in 1988 an...

Radar reflectivity data can be quality-controlled using just the radar moments, and several techniques have been proposed to do this. It is possible to use texture features as inputs to a neural network to discriminate between precipitating radar echoes, and echoes that correspond to clear-air return, ground clutter or anamalous propagation. A texture feature neural network that was recently de...

In this paper, a signal processing technique is developed to reduce clutter due to ground bounce in ground penetrating radar (GPR) measurements. This technique is especially useful when a GPR is used to detect subsurface antipersonnel mines. The GPR clutter is modeled using a simple parametric model. Buried mine and clutter contributions are separated through a pair of coupled iterative procedu...

In this paper, we address the problem of classifying clutter returns into statistically homogeneous subsets. The classification procedures are devised assuming latent variables, which represent classes to each range bin belongs, and three different models for structure covariance matrix. Then, expectation-maximization algorithm is exploited in conjunction with cyclic estimation come up suitable...