摘要
A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation functions. According to values of βi^t（K）, N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, tiros, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and nnkes it possible to be realized on real-thne, Theoretical ,analysis and Monte Carlo simulation results show that this method is efficient.
A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation functions. According to values of βi^t（K）, N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, tiros, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and nnkes it possible to be realized on real-thne, Theoretical ,analysis and Monte Carlo simulation results show that this method is efficient.
