Research On Unmanned Vehicle Collaborative Reconnaissance Strategy And Algorithms For Radar Networks

With the continuous development of modern military technology,radar networking technology has become an important means to deal with the "four threats" composed of stealth targets,anti-radiation missiles,low altitude penetration and integrated electronic jamming.Compared to single radars,networked radars link different radars into a network,combining the reconnaissance advantages of multiple radars to obtain a larger reconnaissance range in the time domain,frequency domain,and airspace.The emergence of radar networking has also brought significant challenges to traditional reconnaissance technology.Single reconnaissance receiver is not sufficient to obtain all relevant parameters of radar networking,and multi reconnaissance receiver distributed collaboration has become an important means for radar networking reconnaissance.This thesis will study the reconnaissance strategies and algorithms for radar networks in the collaborative reconnaissance environment of multiple unmanned carrier mounted reconnaissance receivers.The main work of this thesis is as follows:(1)The conditions of a single radar participating in radar networking are analyzed.Based on these conditions,the signal characteristics of radar networking are analyzed.Different radar networking methods are explained.After providing the radar information features that can be used to determine the radar networking method,the radar information features of different networking methods are analyzed in detail.Corresponding signal parameters are provided based on the characteristics of radar information,and a judgment method for radar networking is proposed based on the analysis of the characteristics of radar networking signals.(2)Corresponding reconnaissance strategies are proposed for radar networking,and the pulse correlation method based on direction finding and multi parameter matching is specifically analyzed.The relationship between pulse correlation accuracy and pulse loss rate is demonstrated through simulation,and the improvement of pulse correlation accuracy is verified when the unknown prior of the target radar is known.(3)The parameter estimation algorithms under multi-station collaboration are studied.Aiming at different parameters in the time and frequency domains,data fusion is carried out using multiple reconnaissance receivers to improve the measurement accuracy of parameters,and the influence of the number of reconnaissance receivers on the data fusion results is studied.Two direction finding algorithms,interferometer direction finding and MUSIC spectrum estimation direction finding,are studied for spatial direction finding.The effects of different factors on the direction finding results are analyzed,and the impact of fusion algorithm after coordinate system conversion on direction finding accuracy is studied during multi machine collaborative direction finding.The TDOA location algorithm based on Taylor series expansion is studied for target radar positioning,and different factors affecting positioning accuracy are analyzed.(4)A polynomial phase modeling and analysis method is proposed for unknown modulation type signals that may appear in radar networks.Firstly,the order of the approximate fitting polynomial phase signal of the unknown signal is estimated.Then,estimate the coefficients of each order of the polynomial phase are estimated after determining the order.The simulation results confirm the feasibility of this method.