Track-Before-Detect Strategy for Radar Detection in Rayleigh-distributed Noise
Liangliang Wang, Gongjian Zhou, Jiazhou He, Thiagalingam T. Kirubarajan · 2019
This paper considers multi-frame radar detection in Rayleigh-distributed noise. Traditional multi-frame track-before-detect (TBD) methods may destroy the radar echo envelope seriously due to its suboptimal accumulation strategy. The integrated envelope may be extended to a large number of cells and cause performance degradation in target detection and parameter estimation. In this paper, we propose a velocity filtering based TBD method to detect and track weak targets for radar systems. Since the radar measurements are complex-valued and the inter-frame accumulation may suffer adversely from the random phase, the envelope detection is used to extract amplitude information firstly. Then, each resolution cell is predicted to the last frame of the processing batch according to an assumed velocity. Amplitude value of the cell is added onto the cell closest to the predicted position for energy integration. The procedure for multi-frame accumulation is presented. The target integrated envelope and false alarm probability of the proposed method in Rayleigh-distributed noise are derived theoretically. The detection threshold is investigated at a constant false alarm rate. Simulation experiments demonstrate the superiority of the proposed method in terms of output envelope focusing, detection performance and estimation accuracy.