A Subspace Method for MIMO Radar Space-Time Adaptive Processing

Abstract

Abstract-In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the MIMO radar system, the transmitter sends noncoherent (possibly orthogonal) broad (possibly omnidirectional) waveforms. These waveforms can be extracted by a matched filterbank. The extracted signals can be used to obtain more diversity or improve the clutter resolution. In this paper, we focus on space-time adaptive processing (STAP) for MIMO radar systems which improves the clutter resolution.With a slight modification, STAP methods for the SIMO radar case can also be used in MIMO radar. However, in the MIMO radar, the rank of the jammer-and-clutter subspace becomes very large, especially the jammer subspace. It affects both the complexity and the convergence of the STAP. In this paper, a new subspace method is proposed. It computes the clutter subspace using the geometry of the problem rather than data and utilizes the block diagonal property of the jammer covariance matrix. Because of fully utilizing the geometry and the structure of the covariance matrix, the method is very effective for STAP in MIMO radar. 1

Low-rank filter and detector for multidimensional data based on an alternative unfolding HOSVD: application to polarimetric STAP

“…Simulations based on signal-tointerference-plus-noise ratio (SINR) losses, probability of detection (Pd), and probability of false alarm (Pfa) showed the interest of our approach: LR filters and LR detectors which can be obtained only from AU-HOSVD outperformed the vectorial approach and those obtained from HOSVD in the general polarimetry physic model (where the channels HH and VV are not completely correlated). The main future work concerns the application of the LR filters and LR detectors developed from the AU-HOSVD for the general system of MIMO-STAP [23][24][25][26].…”

MIMO Radar Detection in Non-Gaussian and Heterogeneous Clutter

“…• depends only on and and not on the clutter parameters, hence showing the texture-CFAR property of the test given by (5). Moreover, it is clear that the detector does not depend on the covariance matrices which can be different for each transmit-receive subarray.…”

“…On top of that, each transmit element sends a different (orthogonal) waveform which can be separated at the receive end. This provides waveform diversity which in turn increases the separation between clutter and target returns [5]. According to [6], it also improves the identifiability of target parameters, enables the direct application of adaptive arrays for target detection, and enhances flexibility for transmit beampattern design.…”

Robust MIMO radar detection for correlated subarrays

“…On top of that, each transmit element sends a different (orthogonal) waveform which can be separated at the receive end. This provides waveform diversity which in turn increases the separation between clutter and target returns [7].…”