Research On Radar Signal Deinterleaving Algorithm In Complex Environment

Radar signal deinterleaving is a key technology in radar signal processing,often applied in electronic countermeasures,electronic reconnaissance and radar environment spectrum analysis.It is used to quickly and accurately extract the relevant feature parameters of radiation sources in a complex electromagnetic environment,and to separate the target radar signals from the interlaced pulse streams to achieve electromagnetic environment spectrum analysis.The effectiveness of radar signal deinterleaving directly affects the overall electronic reconnaissance system decision results.With the development of modern radar technology,the electromagnetic environment becomes more and more complex,the existing radar signal deinterleaving methods face serious challenges.In this paper,we provide an overview of radar signal deinterleaving techniques and algorithms,explore the framework of radar signal deinterleaving in future,and investigate the single-parameter radar signal deinterleaving algorithm,pulse repetition interval(PRI)modulation type,and sequence search for key issues.Firstly,single-parameter radar signal deinterleaving algorithms are investigated.In the complex radar electromagnetic environment,radar signals overlap in frequency domain,time domain as well as air domain.The multi-parameter clustering results still contain multiple radars,making it difficult to deinterleave them.To successfully deinterleave various types of radar signals,this paper proposes a double threshold sequence difference histogram algorithm,which utilizes double thresholds to improve the detection ability of fixed and staggered signals in the case of pulse missing,and performs staggered analysis in the histogram results to improve the efficiency of staggered sequence search.Propose a multi-level PRI bin structure,so that the jittered signal can enter the suitable PRI bin to increase the target radar detection probability and improve the PRI estimation accuracy.For large range special type radar,this paper performs a smooth filtering process based on multi-level PRI bin,combines deep forest prediction network,predicts the range of PRI variation,corrects the PRI estimation,and realizes the deinterleaving of special type radar.The simulation results verify the effectiveness of the proposed algorithms.Secondly,to address the issue that the novel PRI modulation type makes it difficult to extract the relevant radar pulse sequences and the inability to reduce the electromagnetic spatial complexity,an inter-pulse slide radar signal recognition and sequence search algorithm based on the Bi-directional long short-term memory(Bi LSTM)network and time serial association is proposed.The algorithm directly uses the time of arrival multi-level difference to train the network,verifies the results through the sequence search,and discriminates again based on the confusion matrix.According to the recognition result,different time serial association modes are selected to analyze the PRI variation pattern of slide radar signal and complete the pulse sequence search.The simulation results demonstrate that the algorithm has higher recognition accuracy and better pulse search performance.Finally,in order to analyze various radar signal deinterleaving algorithms and compare their performance advantages and disadvantages,we simulate simple,special and complex electromagnetic environments to test the algorithms,and the results prove the excellent performance of the algorithms in this paper.In the meantime,we design and code radar signal deinterleaving simulation software platform,which can simulate 12 different types of radar signals and flexibly generate radar pulse data of electromagnetic environment for deinterleaving,or can choose to import real data.The platform has a wide range of built-in deinterleaving algorithms,including 36 combinations of deinterleaving algorithms,which can be compared horizontally in order to be used more effectively in the study of radar signal deinterleaving.