Research On The Movement Law Of Maritime And Airborne Targets Based On Improved Sparrow Search Algorithm

The research on the movement law of maritime and airborne targets is a systematic observation,analysis,and research on the movement and law of maritime and airborne targets.The importance of this research is reflected in improving our military intelligence collection and surveillance capability and providing strong support for national security through understanding the military aviation as well as maritime movement law of hostile countries or organizations.With the rapid development of UAV technology in recent years,the application of UAVs in maritime and airborne targets movement monitoring and reconnaissance has received increased attention.It can not only improve the monitoring efficiency and accuracy,but also help the monitor to better understand the movement law of the target,to better achieve the tracking and reconnaissance of the target.Therefore,this paper focuses on UAV trajectory planning based on an improved sparrow search algorithm.The main work is as follows:(1)An improved sparrow search algorithm is proposed by comparing and analyzing multiple swarm intelligence optimization algorithms.Chaotic mapping is introduced in this algorithm to replace random sequences to initialize population,increase population diversity and thus improve global optimization accuracy.The sparrow search algorithm is optimized by adaptive T-distribution,which improves the convergence speed and accuracy of the algorithm.(2)The performance of the improved sparrow search algorithm is verified by using test functions.The simulation tests of single peak,multi peak and low dimension test functions show that the performance of sparrow search algorithm can be successfully improved by using Sinusoidal chaotic map.The experimental results show that the improved sparrow search algorithm outperforms the ant colony optimization algorithm,particle swarm optimization algorithm,gray wolf optimization algorithm and the original sparrow search algorithm.(3)A three-dimensional UAV trajectory planning environment model is constructed,focusing on static threats of coastal city buildings and mountain peaks.This paper selects three constraints of minimum path length,minimum safe flight altitude and turning angle to construct the trajectory planning objective function,then transform it into the problem of finding the minimum value of the objective function and construct a three-dimensional static UAV trajectory planning environment model.Finally,a smooth curve with good continuity is obtained after smoothing of the resulting trajectory.(4)The improved sparrow search algorithm and the original sparrow search algorithm are applied to the trajectory planning of unmanned aerial vehicles.By comparing and analyzing the generated trajectory lengths,the results show that the optimization performance of the proposed improved sparrow search algorithm has better performance.