Research On High Precision Location Algorithm For Airborne Emitter Target With Fixed Single Observer

As the useful supplement to active location,passive location has attracted more and more attention.Single-observer passive location system has the advantages of good flexibility,long detection distance,wide range of application and broad development prospects.Taking the airborne emitter as the observation object,this paper uses a single fixed observer to collect the spatial-frequency domain information caused by the relative motion of the target emitter,and carries out the research on the fixed single-observer passive high-precision location and tracking algorithm.The main work includes four aspects:1.The positioning principle based on the observation model of fixed single observer to airborne radiation source is described.The passive ranging formula is derived,and the factors affecting the location error are qualitatively and quantitatively analyzed by using the GDOP.For the key pre-problem of observability of single-observer passive location,the method of pseudo-linearization is used to deal with the nonlinear system,and the observability conditions of the target emitter under the condition of constant velocity,constant acceleration and constant turning are derived.2.In view of the shortcomings of common nonlinear filtering in passive location of uniform cruise emitter targets in terms of stability,convergence speed and robustness,an iterative simplified improved algorithm based on SRCKF is proposed.According to the linear characteristics of the state equation of the observation model,the linear simplification is carried out in the time update link to reduce the operation overhead,and an iterative algorithm is introduced in the measurement update link to make full use of the latest measurements to speed up the convergence speed.The simulation results verify the superior performance of the algorithm.3.In order to solve the problem of complex motion mode of mobile emitter target,a STSRCKF algorithm is proposed.The simulation results show that compared with the SRCKF algorithm,when the target is not maneuvering the STSRCKF algorithm is on the same level,and on the other hand the performance of the STSRCKF algorithm is better when the target is maneuvering.In order to solve the problem that it is difficult for a single model filter to cover the target maneuvering form,the IMM algorithm is combined with the SRCKF algorithm.At the same time,the problem of traditional model transfer lag is improved,and a modified transition probability IMM-SRCKF algorithm is proposed.Simulation results show that the improved algorithm is better in improving model switching speed,filtering accuracy and robustness.4.In order to solve the problem that the actual observed outliers seriously affect the location performance of single-observer passive location system,a robust location and tracking algorithm to suppress the influence of outliers is studied.Inspired by the normalized contaminated normal distribution model(SCNM),its core idea is applied to the improved SRCKF algorithm,and an anti-outlier SRCKF algorithm is proposed.Simulation results show that the improved algorithm can strongly restrain the influence of outliers in observation,and its stability and estimation accuracy remain at a higher level compared with SRCKF algorithm after outliers appear.