Radar Detection Performance Evaluation Based On Big Data

In recent years,with the rapid development of radar technology and data technology and the increasingly frequent use of radar equipment,the amount of data generated is also increasing.Due to the wide application of radar technology in all walks of life,accurate assessment of radar performance is becoming more and more important and of great significance.With the advancement of radar technology,modern radars will generate a large amount of data.However,these radar big data contain a wealth of radar operating status information.If they can be further excavated through data processing technology,it will be of great significance to grasp the real-time status of radar work.At present,radar performance has been evaluated in various fields in scientific research,such as evaluation of radar anti-jamming performance,performance evaluation in the context of sea clutter,performance evaluation in electromagnetic environment,etc.This topic will start with the big data generated by the radar track and evaluates the performance of the radar.This topic mainly includes the following three parts: The first is the evaluation of radar performance in the presence of a real radar track to detect the target.Because AIS is a kind of high-accuracy equipment,AIS data can be used as real track data to correlate with radar data,and radar track data and AIS track data can be compared and processed to evaluate the working performance of the radar.The second is the evaluation of radar performance in the absence of true radar track to detect the value of the target.At this time,there is no accurate target data as a reference.Under this condition,the project uses a modified IMM algorithm to estimate the measured noise of the radar so as to achieve the purpose of radar performance evaluation.Regardless of which of the above two methods are used,we must obtain statistics through a large amount of data.Therefore,in the end,the project uses VC++ and non-relational database(No SQLt)to perform data storage and data processing,so that real-time processing of radar data can be performed in actual work.In the case of real target track data,the first step is to correlate the radar data with the AIS data.The subject adopts the fuzzy comprehensive evaluation method for track association.Based on the distance,azimuth,and velocity information of radar and AIS data,use the membership function to correlate the radar track with the AIS track.After the correlation is successful,the performance of the radar is evaluated through the AIS track information.In the absence of real target track data,the project uses a modified IMM algorithm and multi-model algorithm to estimate the radar measurement noise to complete the radar performance evaluation.Using multiple IMM filters,each IMM filter is initialized with different measured noise values,and the probability of each IMM filter is determined using a multiple model algorithm.The new measured noise is weighted by each IMM filter measurement noise obtain.Update the measured noise value of each filter,and iterate until the estimate of the measured noise converges and stabilizes.Finally,the use of VC++ and No SQLt database to complete the operation of the radar data,and draw a simple track map,in order to complete the real-time data processing needs and data visualization.