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