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In the moving sensor network, the direct positioning method (DPD) can greatly improve the positioning performance of the system, but it also brings the problem of high computational complexity and poor stability of the algorithm. In this paper, a distributed fast DPD algorithm based on timefrequency difference is proposed. The complex large-scale matrix operation and the maximal eigenvalue solution in the original DPD algorithm are replaced by the cross ambiguity function (CAF) and the matrix norm respectively. An effective distributed computing method is designed to make full use of the sensor network Of the computation resources. The simulation results show that the proposed method can greatly simplify the computational complexity, improve the stability of the algorithm , while the location performance is equivalent to the original DPD algorithm. KeywordsDPD; matrix norm; time-frequency difference; cross Ambiguity Function (CAF)

A Fast Distributed Direct Postion Determination Algorithm Based on Delay and Doppler