Abstract
Multi-target detection is the main function of radar. Cognitive radar, which can adaptively investigate the radar scene and determine the next action based on previous measurements, has better performance. In this paper, a multi-target detection method and an adaptive waveform design algorithm for cognitive MIMO radar are proposed. In this method, the multi-target detection is modeled as a multi-hypothesis testing. The multi-hypothesis testing is investigated according to sequentially received data. Along with the multi-target detection method, an adaptive waveform design algorithm based on information theory is proposed to improve the efficiency of the multi-hypothesis testing. We adopt semi-definite relaxation technique and semi-definite programming to tackle the nonconvex design problem. Numerical examples demonstrate that the proposed multi-target detection method has better performance than the classical target detection method, and the proposed adaptive waveform design algorithm can significantly improve the performance of the proposed multi-target detection method.
| Original language | English |
|---|---|
| Article number | 8478352 |
| Pages (from-to) | 9962-9970 |
| Number of pages | 9 |
| Journal | IEEE Sensors Journal |
| Volume | 18 |
| Issue number | 24 |
| DOIs | |
| Publication status | Published - 15 Dec 2018 |
| Externally published | Yes |
Keywords
- Cognitive radar
- MIMO radar
- optimization
- target detection
- waveform design