Abstract:

The increase in the channel number of multiple-input multiple-output (MIMO) radar significantly raises the amount of data transmission and processing burden while improving the target detection performance. In view of the problem of colocated MIMO radar detection of moving targets, firstly, the radar echo data is bit-quantized, and then fusion detection processing is performed. Since the generalized likelihood ratio test (GLRT) requires maximum likelihood estimation (MLE) for the unknown parameters, and there is no closed solution for the MLE of the unknown parameters in the problem above, resulting in a large computational effort for the corresponding test statistics. In this paper, a novel generalized Rao (G-Rao) test is applied, which remarkably reduces the computational effort of the test statistics since there is no need to solve the MLE of the unknown parameters and the corresponding test statistics have a closed-form solution. In addition, to improve the detection performance, the quantization thresholds are optimized using the particle swarm optimization algorithm (PSOA). Finally, experiment results not only verify the effectiveness of the G-Rao detector but also show that, compared with single-bit quantization, the detection performance of a small number of multi-bit quantization is superior to that of the single-bit quantization method while effectively reducing the signal transmission and processing burden.

Key words: multiple input multiple output (MIMO) radar, bit quantization, target detection, generalized Rao test, particle swarm approach