Spectrally Constrained MIMO Radar Waveform Design Based on Mutual Information

We address the waveform design problem for multiple-input multiple-output (MIMO) radar in spectrally crowded environments. We exploit the mutual information between the target reflections and the target responses as the design metric. To tackle the associated nonconvex optimization problem, we propo...

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Bibliographic Details
Published inIEEE transactions on signal processing Vol. 67; no. 3; pp. 821 - 834
Main Authors Tang, Bo, Li, Jian
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Codes
Covariance matrices
Lattice theory
Measurement
MIMO radar
minorization-maximization (MM)
Mutual information
Optimization
Radar
Radar antennas
Radio frequency
Spectra
spectrum crowding
Taylor series
waveform synthesis
Waveforms
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Summary:We address the waveform design problem for multiple-input multiple-output (MIMO) radar in spectrally crowded environments. We exploit the mutual information between the target reflections and the target responses as the design metric. To tackle the associated nonconvex optimization problem, we propose an algorithm based on first-order Taylor series approximation as well as minorization-maximization (MM) based algorithms to design the spectrally constrained waveforms. Interestingly, for some scenarios, we can synthesize the globally optimal (spectrally constrained) waveforms with the maximum mutual information. We also show that, through intelligent waveform design, MIMO radar can coexist more efficiently with other communication systems occupying the same spectrum, while suffering from insignificant mutual information losses.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2018.2887186