Transmit Waveform/Receive Filter Design for MIMO Radar With Multiple Waveform Constraints

In this paper, we consider the joint design of both transmit waveforms and receive filters for a colocated multiple-input-multiple-output (MIMO) radar with the existence of signal-dependent interference and white noise. The design problem is formulated into a maximization of the signal-to-interferen...

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Veröffentlicht in:IEEE transactions on signal processing Jg. 66; H. 6; S. 1526 - 1540
Hauptverfasser: Wu, Linlong, Babu, Prabhu, Palomar, Daniel P.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 15.03.2018
Schlagworte:
Algorithm design and analysis
Convergence
Interference
joint design
majorization-minimization (MM)
MIMO radar
Radar antennas
Signal to noise ratio
SINR maximization
waveform constraints
ISSN:1053-587X, 1941-0476
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Zusammenfassung:In this paper, we consider the joint design of both transmit waveforms and receive filters for a colocated multiple-input-multiple-output (MIMO) radar with the existence of signal-dependent interference and white noise. The design problem is formulated into a maximization of the signal-to-interference-plus-noise ratio (SINR), including various constraints on the transmit waveforms. Compared with the traditional alternating semidefinite relaxation approach, a general and flexible algorithm is proposed based on the majorization-minimization method with guaranteed monotonicity, lower computational complexity per iteration and/or convergence to a B-stationary point. Many waveform constraints can be flexibly incorporated into the algorithm with only a few modifications. Furthermore, the connection between the proposed algorithm and the alternating optimization approach is revealed. Finally, the proposed algorithm is evaluated via numerical experiments in terms of SINR performance, ambiguity function, computational time, and properties of the designed waveforms. The experiment results show that the proposed algorithms are faster in terms of running time and meanwhile achieve as good SINR performance as the the existing methods.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2017.2787115