Research On Multi-station Passive Location Method For UAV Target Based On Received Signal Strength Difference

As an emerging fast-developing electronic countermeasure technology,passive location tracking technology is an important research content of multi-sensor data fusion.Usually coordinated by multiple reconnaissance stations,the location or tracking of unknown radiation source targets can be quickly achieved.Due to simple data acquisition,low hardware requirements,low cost,and low power consumption,multi-station passive positioning algorithms based on received signal strength differences have been more and more widely studied.The method requires signal strength numerical processing,environmental parameter estimation,multi-station information fusion positioning and other processes,and the key is signal strength numerical processing and measurement of relevant environmental parameters.Since the signal strength of the radiation source is unknown,it is not possible to rely directly on the observations of each signal strength observatory to directly locate the target of the radiation source.Therefore,we consider using the difference information between the observations of each observatory to achieve radiation.The position estimate of the source target is considered,and the estimated position is corrected in combination with the high-precision direction finding result.Based on the UAV positioning system,this paper studies the positioning and tracking algorithm of the UAV.The main contents are as follows:(1)The basic theory of multi-station passive positioning technology based on received signal strength is studied.The existing free-space propagation model,doubleray ground reflection model and log-normal attenuation shadow model are used to signal strength path loss model.The characteristics were analyzed and studied,and the applicable environmental categories of different models in practical engineering problems were discussed.In order to improve the positioning accuracy of the radiation source target,the logarithmic normal attenuation shadow model is finally selected as the basis for the next algorithm research.Two critical environmental parameters in the lognormally attenuated shadow model are then estimated.A Gaussian model outlier elimination method and a statistical median method are proposed to deal with the two kinds of signal strength random observation data.Based on the multi-station received signal strength,the nonlinear optimization problem of positioning is transformed into a pseudo-linear least squares estimation problem,and the initial value localization method of RSSD(received signal strength difference)is derived.And analyze the degree of deviation between the initial value coordinates and the target position under different noise levels.(2)Firstly,when the target transmission power is unknown,the nonlinear optimization problem based on multi-station received signal strength localization is converted into pseudo-linear least squares estimation problem,and the RSSD(received signal strength difference)pseudo-linear minimum is derived.Two-way positioning method.And analyze the degree of deviation of the estimated coordinates from the target position under different noise levels.Secondly,based on the RSSD pseudo-linear least squares localization method,two kinds of pairs of radiation based on the RSSD pseudolinear least squares multi-initial value Gauss Newton iterative correction method and the RSSD pseudo-linear least squares multi-initial value construction pseudo-iteration iterative correction method are proposed.The exact calculation method of the source target position.The latter two algorithms combine the advantages of the three separate positioning,while taking advantage of the long complement,the algorithm performance has achieved a leap.The theoretical and simulation analysis shows that the two algorithms proposed in this chapter can better adapt to the high noise level positioning environment,and can meet the high precision positioning requirements and real-time.(3)The multi-station received signal strength difference and single-station direction finding fusion localization algorithm for UAV targets are studied.Firstly,mathematical models of received signal strength difference and direction finding are established respectively.Based on the analysis of advantages and disadvantages and positioning performance,the proposed algorithm is used to calculate the received signal strength difference and the direction-finding fusion localization algorithm.The algorithm uses the RSSD pseudo-linear least squares localization model to solve the initial value and then returns the station positioning model to obtain the equivalent.The transmitted signal strength is combined.The direction finding result achieves accurate positioning.The algorithm combines the advantages of the first two algorithms.The positioning accuracy is high and can meet the real-time performance.Finally,the performance of the algorithm is verified by simulation experiments.(4)Applying the received signal strength difference and the direction finding fusion positioning algorithm to the passive positioning system.Summarizes the functions that the system can achieve,as well as the actual positioning effect.