Research On Key Techniques Of Passive Localization For High-speed Maneuvering Emitter

The practice of modern high-tech local war indicates that it is vital to covertly,efficiently and accurately obtain the battle-field situation.In view of this,passive localization has gradually become one of the important means of situation awareness and target information acquisition.Recently,more and more enemy air military targets are deployed around China,which seriously threaten the national security.Against this background,effective surveillance,intent judgments and situation predictions for aerial high-speed maneuvering targets has become research hotspots and development trends,so as to improve the national air space defense capability.Based on the characteristics of high-speed maneuvering emitters,this paper makes full use of dynamic conditions and non-linear information,and focuses on the difficult problems of multi-station pulse sorting and pairing,parameter estimation of dynamic carrier-constant signal,parameter estimation of dynamic frequency-hopping(FH)signal,and robust target localization.This research improves and enriches the framework of passive localization,and provides theoretical support for signal sorting,parameter estimation and localization in multi-station passive localization of high-speed maneuvering targets.The main work of this paper is as follows:1.Considering the problem of high false alarm rate and high missing alarm rate for sorting the pulse with ultra-low pulse repetition frequency in conventional time difference of arrival(TDOA)-based sorting methods,this paper proposes a pulse sorting and pairing method based on constrained extended TDOA histogram.In this method,a constraint condition with respect to pulse parameters is firstly introduced to obtain the valid TDOA distribution.Then,the extended iteration operation is used to sequentially complete the pulse sorting and pairing of each emitter.After reducing the chance of irrelevant pulse pairing by the constraint condition,the proposed method fundamentally decreases the number of false TDOA and noise TDOA,and effectively suppresses the generation of false emitters.Numerical experiments indicate that compared with the existing methods,the proposed method can significantly improve the performance of TDOA sorting and can achieve the accurate sorting and pairing for the pulse with ultra-low pulse repetition frequency pulses even a single pulse.2.Considering the high computational complexity,serious signal to noise ratio(SNR)loss and low estimation accuracy of the existing dynamic parameter estimation algorithms,this paper proposes a joint estimation algorithm of range difference(RD)and range difference rate(RDR)based on frequency symmetric autocorrelation function and scaled Fourier transform(FSAF-SFT).This algorithm can fulfill the parameter estimation without any searching process.For the high-speed maneuvering emitter with complex motion,the second-order range difference rate(SRDR)should be considered due to the improved dynamics of the received signals.From two aspects of efficiency and accuracy,this paper respectively proposes two estimators: first one is based on second-order keystone transform and Lv's distribution(SKT-LVD);another one is based on SKT and non-uniform Fourier transform(SKT-NUFFTT).Both methods can efficiently eliminate the complex range migration and Doppler frequency migration of high-speed maneuvering target.Meanwhile,they can also avoid the use of constant delay correlation operation,which significantly improve the anti-noise performance compared with the existing algorithms.The proposed SKT-LVD achieves a good balance between computational complexity and estimation performance.The SKT-NUFFT can acquire comparable estimation performance with the ideal maximum likelihood estimator,but the complexity has slightly increased.In practical applications,algorithms can be selected according to requirements.3.Considering the weak adaptability of high dynamic scene,the frequency difference jump,the limited signal available length and the low estimation accuracy of the existing estimators for FH signals,this paper establishes a time-varying baseline estimation model for FH signals,and proposes a joint RD and RDR estimation algorithm based on frequency reversing transform and scaled Fourier transform(FRT-SFT).This algorithm uses FRT to eliminate the random phase caused by frequency hopping,and then the SFT is used to correct the range migration,which can effectively accumulate all the pulses,and improve the estimation performance.For the high-speed maneuvering FH emitter,it is necessary to overcome both high dynamic characteristics and random Doppler frequency migration.Therefore,this paper proposes a joint RD,RDR and SRDR estimation algorithm of FH signal based on SFT and scaled non-uniform fast Fourier transform(SFT-SNUFFT).This method can remove the random Doppler frequency migration and improve signal coherence with the help of variable frequency cross-correlation function.After that,the SFT and SNUFFT are used to correct the range migration and accumulate the signal energy two times to fulfill the parameter estimation.Simulation results show that the algorithms can adapt to the high dynamic scenes,and the estimation performance is significantly better than the existing algorithms.In addition,the above two algorithms can estimate RD,RDR and SRDR without using prior information about the carrier frequency,which can be directly used for target localization,rather than estimating the traditional time difference of arrival(TDOA),frequency difference of arrival(FDOA)and differential Doppler rate(DDR).Moreover,it can effectively overcome the problem of FDOA and DDR changing in FH signals.4.Considering the problem of poor robustness and positioning parameter underutilization for moving source localization of the traditional methods,this paper proposes an algebraic method for moving source localization using RD,RDR and SRDR measurements based on two-step weighted least squares(TSWLS).The algorithm follows the basic framework of two-step weighted least squares.It can effectively linear three types of localization equations by introducing auxiliary parameters,and obtain the initial result with the help of weighted least squares;then,by using the relationship between auxiliary parameters and target position and velocity,the linear equation is constructed again to further improve the localization accuracy.On this basis,considering the receiver location errors,we extend the location model and design a localization method in the presence of receiver location errors.A new Cramér-Rao lower bound(CRLB)combining RD,RDR and SRDR with receiver location errors is also derived in this paper.Theoretical analysis and simulation results both indicate that the proposed method can attain CRLB at a moderate noise level,efficiently avoid the rank deficiency problem,and achieve a significant improvement over the existing methods without any iterative process.