Performance analysis of adaptive range-spread target detector in extremely training-deficient scenarios

Adaptive detection of range-spread target is discussed in the extremely training-deficient scenarios. The performance analysis of the detector without training data is conducted by Monte Carlo simulation. It implies that, the detector performs robustly for different correlations of clutter and for different target scatterer models. Furthermore, the detection performance improves as the number of channels used decreases or the range extent of target increases. In addition, the detection performance decreases as the fluctuation degree or the correlation degree of target scatterers strengthens for high detection probability, while increasing with weakening fluctuation or correlation for low detection probability.