Abstract
Low-correlation sidelobes are critical for spectrally compatible waveforms in multiple-input multiple-output (MIMO) radar systems. This study presents a novel algorithm for designing spectrally compatible waveforms for MIMO radar with low auto- and cross-correlation sidelobes to enhance weak target detection capability. We adopt the minimum auto- and cross-correlation-weighted integrated sidelobe level (ACWISL) as the objective function. Under spectral and constant modulus constraints, we formulate a nondeterministic polynomial time (NP)-hard problem. To solve this problem, we combine the block successive upper-bound minimisation (BSUM) and majorisation-minimisation (MM) algorithms to develop the BSUM-MM algorithm. The original problem is decomposed into several independent subproblems, which are iteratively solved using the MM algorithm. We also employ the fast Fourier transform (FFT) to significantly accelerate the calculation. Simulation results demonstrate that the proposed algorithm is superior in terms of computational efficiency and sidelobe performance.
| Original language | English |
|---|---|
| Article number | e70024 |
| Journal | IET Radar, Sonar and Navigation |
| Volume | 19 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2025 |
| Externally published | Yes |
Keywords
- array signal processing
- radar
- radar signal processing
- radar waveforms
- signal processing
- waveform analysis
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