Study On Collaborative Target Detection In Multistatic Radar

Radar is an important means of gathering information on modern battlefield intelligence.Conventional monostatic radar cannot obtain sufficient target information due to its single viewing angle.With the rapid development of electronic countermeasures technique,monostatic radar also reveals obvious deficiencies in terms of survivability and antiinterference ability.Compared with monostatic radar,multistatic radar has great advantages in collaborative target detection,anti-electronic reconnaissance and anti-interference ability.In this dissertation,taking multistatic radar as the research object and applying the signal fusion-based detection technique,several interesting problems of collaborative target detection in multistatic radar are studied.The main work of this dissertation includes the following four aspects:1.Key concepts of collaborative target detection in multistatic radar are introduced,including target radar cross section(RCS)fluctuation characteristics,target signal decorrelation conditions and multi-channel detector designing technique.In summary,target RCS fluctuation is a prerequisite for multistatic radar to improve the target detection performance by using spatial diversity gain.Target signal decorrelation conditions provide a theoretical basis for actual site selection of multistatic radar.Multi-channel detector designing technique lays the foundation for solving specific detecting problems.2.A general processing framework for signal fusion-based detection in multistatic radar is proposed.First of all,starting from a more realistic physical scene,the problem of signal fusion-based detection using the observation data from different radar sites is investigated.Considering the difference of spatial resolution cell(SRC)between monostatic and multistatic radar,the size of multistatic SRC is discussed.Based on this,the framework definition of signal fusion-based detection in multistatic radar is given,mainly including the definition of space mapping,the concepts of family,branch and relatives,the definition of target response.Next,the proposed framework for signal fusion-based detection in multistatic radar is applied to a non-coherent integration(NCI)detector,and detailed case analysis is performed.Finally,the performance of the peak search method in deciding which multistatic SRC on earth contains the target of interest is studied.3.The adaptive constant false alarm ratio(CFAR)processing for multistatic radar under the situation of spatial registration errors is studied.First of all,considering that perfect spatial registration is hard to achieve in practical engineering,a target measurement model with spatial registration errors is established.Next,under the framework of two-step generalized likelihood ratio test(TS-GLRT),two kinds of adaptive multi-channel detectors that are robust to spatial registration errors are designed,namely ML-GLRT detector and MAP-GLRT detector.The main difference is whether they use a priori information of spatial registration errors.Theoretical analysis demonstrates that both proposed detectors can maintain CFAR property.Furthermore,experimental results show that both two detectors outperform conventional NCI detector in presence of spatial registration errors.4.Target detection and angle measurement in mainlobe and sidelobe jamming environment for multistatic radar are discussed.First of all,starting from a more practical interference scene,the problem of effective jamming suppression and target detection in presence of both mainlobe and sidelobe jamming using multistatic radar is investigated.In this case,a basic anti-jamming idea is that each radar station locally performs adaptive sidelobe nulling with mainlobe maintenance,and then transmits the remaining mainlobe signal,including both mainlobe jamming and target signal,to the signal fusion center for joint processing.According to this idea,a general processing flow for multistatic radar target detection in presence of both mainlobe and sidelobe jamming is provided,which mainly includes two parts: local sidelobe adaptive nulling with mainlobe maintenance,and global inner-station mainlobe jamming suppression.Next,the problem of false targets discrimination derived from the process of mainlobe jamming cancellation is briefly discussed,and an effective strategy for false targets excision is given.Finally,the proposed mainlobe and sidelobe jamming mitigation algorithm is applied to a monopulse estimator,and the corresponding monopulse response curve(MRC)is derived.