Research On Radar Signal Sorting Algorithm Based On Multi-station Collaboration

Radar signal sorting,as an important component of electronic reconnaissance,plays a crucial role.High quality signal sorting is the foundation and prerequisite for achieving signal analysis and recognition.With the continuous progress of radar technology,the complexity of the electromagnetic environment is gradually increasing,and the ability to correctly and efficiently sort signals has become an urgent problem to be solved in electronic countermeasures.In the current dense,complex,and ever-changing electronic warfare signal environment,pulse signals emitted by different radiation sources often form dense and overlapping pulse streams after being processed by the front-end of reconnaissance and reception equipment.With the increasing emergence of new system radiation sources,the complex and ever-changing signal waveforms and severely overlapping feature parameters make current single station signal sorting unable to fully meet the sorting requirements of complex battlefield environments.In the context of multi station collaborative reconnaissance,this article improves the traditional multi station collaborative sorting algorithm based on time difference,and proposes a station location optimization algorithm to address the problem of time difference ambiguity in target sorting of formation radiation sources.The main content of this article can be divided into the following two points:(1)In response to the problems of false alarms and low accuracy in traditional multi station collaborative sorting algorithms based on time difference histograms,which utilize fixed group spacing for time difference statistics,this paper proposes a recursive sorting algorithm for estimating the k-nearest neighbor of the time difference center.Firstly,the time difference vectors of each radiation source pulse arriving at different reconnaissance stations are formed into a set of time difference vectors.Based on the fact that the time difference of the same radiation source pulse is always distributed around its true time difference,the distance average of the nearest neighbors of the time difference vector k is calculated,and the time difference vector with the smallest distance average of the nearest neighbors of k is used as the initial time difference center,thus achieving preliminary estimation of the time difference center.Then,based on the current time difference center,merge the time differences within the distance threshold in the order of k-nearest neighbor distance mean from small to large,and calculate the average value of the time difference vector to update the time difference center in real-time.Finally,sort the time difference clusters merged based on the current time difference center,and remove the corresponding time difference from the time difference vector set.Select a new time difference center and repeat the above steps for recursion to sort out each radiation source pulse.In response to the problem of missed pulse selection caused by pulse loss in multi station time difference selection,this article utilizes a time difference vector dimensionality reduction and merging module to improve it.Firstly,based on the algorithm proposed in this article,the complete dimensional time difference vectors generated by successfully matched pulses are preliminarily sorted.Then compare the time difference vector caused by pulse loss with the time difference center of the corresponding dimension of the preliminarily sorted radiation source,and merge the time differences within the distance threshold to reduce the number of missed pulses.The simulation results show that the signal sorting performance of the algorithm proposed in this paper is superior to the traditional time difference histogram algorithm.Combining the time difference vector dimensionality reduction and merging module in pulse loss environments can effectively improve the problem of pulse miss selection.(2)This paper proposes a three-station sorting site optimization algorithm based on fuzzy region minimization to address the problem of time difference feature ambiguity in collaborative sorting.Firstly,the mathematical conditions that the time difference fuzzy area of the radiation source satisfies are derived,and at the same time,the time difference fuzzy area of the known radiation source in the dual reconnaissance station is modeled and simulated.Then,based on the dual reconnaissance stations,the intersection of two fuzzy regions generated by the three stations is used to further reduce the time difference fuzzy region.The intersection point of the two fuzzy region boundaries is solved using the Chan algorithm,and the area of the three station time difference fuzzy region is calculated.Finally,in order to reduce the area of the blurred area and improve the performance of the three station sorting time difference ambiguity resolution,the effects of station baseline length,time difference measurement error,and radiation source position on the area of the time difference blurred area were investigated.The search optimization function was used to optimize the location of the target radiation source,that is,to minimize the area of the fuzzy area.Based on this,the distribution characteristics of the optimized site were optimized for key reconnaissance areas according to the different locations of the target radiation source.The simulation results show that the longer the baseline length of the station and the smaller the measurement error of the time difference,the smaller the fuzzy area of the three station time difference.Compared with traditional triangular and linear station layouts,when the baseline length and measurement error of the station are fixed,sorting based on the optimized station location proposed in this article can effectively improve the ability to sort dense radiation source formations.