The Deception ECCM In Multiple-radar Systems

The radar electronic counter-countermeasure(ECCM)provides important guarantee for the survival and operation of radar in complicated electromagnetic jamming environments.Due to its high energy and cost efficiency,deception jamming has been playing an increasingly important role in the radar electronic countermeasure(ECM).The ECCM ability of monostatic radar is limited caused by its single view angle.Therefore,multiple-radar architectures inevitably become the major development tendency,in which information of each target from all radar stations is fused and jointly processed.Because of its spatial diversity,the multiple-radar system has natural advantage of countering deception jamming,and can effectively improve the discrimination performance of active false targets.In this dissertation,the theory and techniques for the deception ECCM in multiple-radar system are researched from the two aspects,i.e.data fusion-based method and signal fusion-based method,which are supported by National Defense Basic Scientific Research,named ”XXX ECCM techniques”.The main content of this dissertation is summarized as follows.· According to the correlation characteristics of real targets in spatial location and velocity vector,the first part focuses on the deception ECCM based on data fusion.The main work includes: 1)In the isostructural netted radar,the discrimination performances of the existing dot fusion-based methods significantly deteriorate for the false targets in far field.For this problem,a new target discrimination method is proposed by fusing the target measurements based on both the spatial location and velocity vector,which obviously improves the discrimination ratio for false targets.2)In the multistatic netted radar,choosing the mahalanobis distance as the discrimination statistic,a false target discrimination method is proposed based on the chi-square test,which can effectively discriminate cooperative false target exploiting the measurements from the receiving stations.3)In the active/passive netted radar,a target discrimination method based on the azimuth-elevation two-dimensional angle statistic is proposed in this dissertation.Compared with the available azimuth angle statistic-based discrimination method,the degree of freedom of the statistic is increased,and therefore the proposed method can obtain a higher discrimination ratio for false targets with the real targets rejection ratio being constant.· The second part researches on the signal fusion-based deception ECCM technique based on correlation test between the complex envelopes of arbitrary two targets in different receivers.The echoes of real targets received by the widely separated stations would be independent or decorrelated due to the fluctuation of radar cross section(RCSs)in different scattering directions.However,the deception jamming received by the stations would be highly correlated.In order to describe this difference,target slow-time complex envelope sequence is defined,which is composed of the complex envelope of the range cell where the target exits during several consecutive pulse repetition intervals(PRIs).Firstly,in the situation of the independent echoes of real targets,a false target discrimination method is presented using experiential threshold,which has simple discrimination processing with satisfied computational costs,but can not achieve an expected real targets rejection ratio.Therefore,we propose a novel discrimination method using adaptive threshold.The sequence mutual correlation is chosen as the statistic.By deriving its probability density function,the designed adaptive threshold can effectively discriminate false targets with the real targets rejection ratio being constant.Finally,the proposed adaptive threshold-based discrimination method is generalized to the situation of the partly correlated echoes of real targets,and its performance improvement over the data fusion-based methods is verified by simulations.The main merits of this kind of discrimination approach lies in that it works for false targets generated by deception signal with arbitrary modulation,since the modulation strategies do not affect the spatial scattering properties.Besides,after being countered by these methods,false targets can be discriminated by the data fusion-based methods to raise the discrimination ratio further.· The third part is contributed to the signal fusion-based deception ECCM method based on cluster analysis in the situation of one PRI.The correlation test-based methods need multiple PRIs to estimate the correlations,which leads to its sensitive to the amplitude and phase error in different stations,and the slow fluctuating targets will be misjudged as deceptive targets.These restrictions in applications motivate us to propose new discrimination methods with only one PRI.The amplitude ratio across different receivers of real and false target is firstly analyzed,and a feature space is established with amplitude ratio among different receivers,in which all false targets concentrate on the same position,while real targets disperse randomly.Based on this phenomenon,hierarchical clustering analysis approach is utilized to discriminate active false targets.In the clustering results,all false targets gather into one cluster and each real target forms a single cluster.Hence,the cluster with more than one target is the false target cluster,i.e.the targets in this cluster are all judged as false targets.Moreover,in the especial cases of self-protect jammer and target overlap,its discrimination performance is analyzed.Finally,simulations verify that the proposed method can effectively discriminate false target within one PRI,solving the aforementioned problem of the correlation test-based methods,but possessing all their merits.· The proposed two kinds of signal fusion-based deception ECCM method work only when radar stations detect the targets independently.When multiple-radar architectures apply cooperative detection as a joint system,the fourth part focuses on signal fusion-based deception ECCM methods based on likelihood ratio test and parameter estimation.The main work includes: 1)Target discrimination is executed in cooperative detection stage.Due to the dependence of deception signals,all received jamming signal vectors exist in a rank one subspace determined by a unified jamming steering vector.On the contrary,the received target signal vectors randomly distribute in the whole space.With the difference,this dissertation discriminates deception jamming from the cooperative detection based on a generalized likelihood ratio test(GLRT)in classical linear models.Simulation results verify the feasibility of the new discriminator.2)When the correlation of target echoes in different receivers become higher,the discrimination ratio of the last method become lower.In this case,we consider applying target discrimination in parameter estimation stage.The unified parameter estimation model is firstly established in multiple-radar systems.Then,the Cramer-Rao lower bound(CRLB)for the deception parameter is derived to evaluate the estimation accuracy,and an indirect iterative estimate method is presented.According to its CRLB and estimation,the discrimination algorithm in parameter estimation stage is designed,and simulation verifies its feasibility and effectiveness.