Research into Track Prediction of Multiple Passive Ship Radar Based on SSA+UKF Algorithm
There are problems such as low detection probability,poor prediction accuracy and high tracking difficulty while detecting and tracking single rapidly moving target and multiple targets with moving trajectory at sea by using traditional ship radars.The accuracy of trajectory prediction can be significantly improved by configuring multiple passive ship radars for real-time detection and effectively fusing received information.By modeling the multiple passive ship radars,this arti-cle uses the salp swarm algorithm(SSA)to predict the trajectory status of multiple ships,and uses unscented Kalman filter(UKF)to perform timely intervention to the factor evaluation course dur-ing the optimization process,which reduces the probability that the estimated value is actually the local optimal value.Simulation experiments show that this algorithm can effectively predict the trajectory of multiple moving targets on the sea,and the accuracy of parameter estimation is high-er.
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