Threshold determination for dynamic programming based track-before-detect in passive bistatic radar

Track-before-detect (TBD) is effective on weak target detection in passive bistatic radar (PBR). The probability of false alarm (PFA) and the probability of detection (PD) in TBD based on dynamic programming algorithm (DPA) are determined by threshold. The extreme value theory and generalized Pareto distribution are usually used to obtain the relationship between PD, PFA and threshold. However, DPA must be performed several times to estimate parameters resulting in much processing time. An iterative method based on Gaussian distribution is another solution but is not suitable for the Chi-square distribution in PBR. Therefore fast threshold determination methods without Gaussian assumption are proposed in this paper. First, a data simulation method is presented. Then an approximation of PD is introduced to further reduce the complexity. Moreover, empirical formulas based on the hypothesis of Chi-square distribution are developed for real-time processing. Simulations verify that the methods are more suitable for real-time processing.