Joint Source Number Detection and DOA Track Using Particle Filter
Dexiu Hu, Yongjun Zhao, Donghai Li · 2010
Current particle filter assumes that the dimension of state is known and constant and it fails when this suppose does not holds. This paper improves on the particle filter using RJMCMC. The improved particle filter can not only preserve the performance on the Non-Linear and Non-Gaussian condition, but also can be used when the dimension of state is unknown or changing over time. This paper uses the improved particle filter in joint direction-of-arrival(DOA) track and source number detection and makes Simulation which shows that the algorithm is effective.