MIMO Radar Transmit-Receive Design for Moving Target Detection in Signal-Dependent Clutter

This paper deals with the joint design of Multiple-Input Multiple-Output (MIMO) Space-Time Transmit Code (STTC) and Space-Time Receive Filter (STRF) to improve the detectability of a moving target embedded in signal-dependent clutter in the presence of uncertainties on the target azimuth angle and D...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 69; no. 1; pp. 522 - 536
Main Authors: Yu, Xianxiang, Cui, Guolong, Yang, Jing, Kong, Lingjiang
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Alternating Direction Penalty Method (ADPM)
Azimuth
Clutter
Eigenvalues
Figure of merit
Iterative methods
Multiple-Input Multiple-Output (MIMO) radar
Object detection
Optimization
Polynomials
Signal to noise ratio
Signal-Dependent Clutter
Space-Time Transmit Code (STTC) Design
Spacetime
Successive Greedy Optimization (SGO)
Target detection
Transmitting antennas
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:This paper deals with the joint design of Multiple-Input Multiple-Output (MIMO) Space-Time Transmit Code (STTC) and Space-Time Receive Filter (STRF) to improve the detectability of a moving target embedded in signal-dependent clutter in the presence of uncertainties on the target azimuth angle and Doppler frequency. The Signal to Interference plus Noise Ratio (SINR) is considered as a figure of merit to maximize and multiple restrictions on STTC are forced at the design stage, i.e., similarity and modulus constraints as well as a uniform power requirement among the transmit antennas. To deal with the resulting non-convex design problem, a novel polynomial-time iterative procedure based on Successive Greedy Optimization (SGO) framework ensuring that SINR monotonically increases and converges to a finite value, is developed. Each iteration of the proposed algorithm involves the generalized eigenvalue decomposition to design STRF and a nested iterative technique involving Dinkelbach's procedure and an Alternating Direction Penalty Method (ADPM) to obtain STTC. Numerical results are provided to assess the performance of the proposed algorithm against some counterparts in terms of the optimized SINR value and computational complexity.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2019.2951399