Research On EWA Environmental Cognitive Method And WAS Moving Target Secondary Detection

The airborne surveillance radar working in Wide Area Surveillance-Ground Moving Target Indication(WAS-GMTI)mode can image a wide range of scenes in the surveillance area,and at the same time detect,locate,track and identify moving targets in the surveillance area.WAS-GMTI mode usually uses Doppler Beam Sharpening(DBS)technology for imaging the monitoring area.This technology has the advantages of small calculation amount and fast imaging speed.It can often obtain a resolution much better than real-aperture imaging,which plays an important role in the field of airborne surveillance.Early warning aircraft radar is another type of long-range detection radar.Because it needs to detect hundreds of kilometers of air targets,the beam is pointed almost horizontally.Although the echo also contains a large number of ground echoes,due to the distance ambiguity,it is impossible to use DBS technology to the ground area covered by the beam.However,trying to apply DBS technology to early warning aircraft data to extract the characteristics of some clutter in the echo,which can provide useful information for subsequent knowledge-aided clutter suppression and other processes,and can be used as an important means for the radar system to recognize the environment.Therefore,it is of great significance to carry out research on DBS information extraction technology for early warning aircraft data.On the other hand,when the battlefield surveillance radar working in WAS-GMTI mode detects and locates ground moving targets,the false alarm caused by discrete strong clutter points in the actual scene remains high.The methods of false alarm suppression in the existing literature have the disadvantages of large amount of calculation or low detection efficiency.Therefore,it is also an important research direction to seek a secondary detection method of targets with small calculation amount and high detection efficiency.Based on the DBS imaging technology and GMTI technology in the WAS-GMTI mode,this paper proposes a method for the early warning aircraft radar to use the improved DBS technology for system environment awareness,and the secondary detection method of moving targets for eliminating the false alarm in the battlefield surveillance radar working in WAS mode.The specific content of the paper is as follows: 1.Aiming at the situation that the multi-frequency operation of the early warning aircraft radar and the distance of the scene echo are ambiguous,a method of extracting clutter information is proposed by using the correlation of the multi-frequency data.This method first obtains distance Doppler data with the same Doppler resolution based on the echo data of multiple frequencies,and then performs period extension in the distance dimension,and then combines the 2/4 criterion with the minimum power criterion,maximum power criterion,and average power criterion to obtain the full-distance dimension data under each criterion,and finally analyzes the strength-and-weakness logic of the full-dimensional data under different criteria and applies DBS technology to implement feature information extraction.The processing results of measured data verify the effectiveness of the algorithm.The information extraction results are in good agreement with the map analysis results.2.Aiming at the problem that there are many false alarms for ground moving targets detection by airborne battlefield surveillance radar,a secondary target detection method based on multi-beam formation is proposed.This method uses the characteristics difference between the echo of the moving targes and the discrete strong clutter points,and forms multiple beam pointing within a specified angle range,and determines whether the detection result is a false alarm by comparing the output power differences between the main beam and the multibeam.Finally,experiments were performed using simulation data.The results show that the method has a small calculation amount,can effectively reduce false alarms caused by strong clutter points,and improves the performance of moving target detection.