Research On Passive Location Algorithm Based On Phase Difference Rate Of Change

In the modern warfare,the electromagnetic environment is increasingly complex,and the traditional active location technology is difficult to adapt to the complex and ever-changing battlefield needs.The passive location system itself does not emit electromagnetic waves,but passively processes the received signals.It has the advantages of high concealment and long-distance warfare,attracting the attention of many scholars.Among many passive location technologies,single-station passive location technology does not need to consider the problem of data transmission and synchronization between multiple stations and the flexibility of its own system,thus becoming a hot research direction in passive location technology.In this paper,the single-station passive location technology based on the phase difference change rate is selected as the research direction.The main work of this paper is as follows:The value and significance of passive location technology research are analyzed,and the development history and research status of passive location technology at home and abroad are tracked.The principle,advantages and disadvantages of several existing single-station passive location methods are briefly introduced.The theoretical basis for selecting the phase difference rate-based location method as the research focus is provided.In this paper,the one-dimensional interferometer positioning model is taken as the starting point,and its feasibility,advantages and disadvantages are analyzed.Then the orthogonal double baseline location model is introduced and the attitude transformation parameters are added.The principle of positioning of orthogonal interferometer in two-dimensional plane under attitude transformation is studied and the formula of geometric accuracy of positioning accuracy(GDOP)is derived.The ambiguity phenomenon of phase difference data measured by interferometer is analyzed,and two methods of ambiguity elimination are given.Then,according to the extraction problem of phase difference rate,four extraction schemes are given.The simulation analysis proves that the differential-Kalman filtering method is the most accurate phase difference rate extraction method.This paper designs two filtering schemes.Firstly,the Kalman filter model is designed by using the location result of single positioning as the observation,and the positioning performance of the two models under different tracks is compared.Secondly,under different tracks,two nonlinear filtering algorithms,EKF(Extended Kalman Filter)and MVEKF(Modified Variance EKF),are used to compare the filters.Experiments show that the MVEKF algorithm has better positioning performance.Aiming at the characteristics that the attitude transformation affects the location accuracy in the positioning method in the previous chapter,an algorithm that only measures the phase difference rate is introduced.This method can realize high-precision solution in the large attitude angle change rate.