Joint Detection and State Estimation of Doppler Radar

In order to improve the performance of Doppler echo signal's detection and parameter estimation under low signal-to-noise ratio (SNR), a joint detection and state estimation algorithm based on random finite set is proposed. Under the framework of formal Bernoulli filter, the target state model and observation model are designed at the Doppler echo signal level, which overcomes the problem that the traditional Detect-Before-track (DBT) method fails due to the loss of target information in the case of low SNR. The time update and observation update of state vector are realized by sequential Monte Carlo (SMC), and the joint detection and state parameter estimation of single target are realized. Simulation results show that the algorithm can effectively improve the performance of detection and state estimation.