Analysis on Performance of Underwater Terrain Aided Navigation Using PMF Algorithm
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摘要: 针对目前水下地形辅助导航性能受诸多因素影响而无法得到最佳发挥的问题, 采用双线性插值法制备了相应分辨率的水下数字地图, 基于直接概率准则的质点滤波(PMF)算法, 较为全面地仿真分析了水下航行器航速、测深误差、航向误差、速度误差、初始位置偏差, 以及水下地形特征等因素对导航性能的影响规律, 对PMF算法在复杂条件下的应用性能进行了剖析。仿真结果表明, PMF匹配算法在复杂条件下具有较强的稳定性; 一定范围内, 该算法对速度和航向表现出较好的抗误差能力, 但速度太低会严重影响匹配性能; 该算法受测深误差和初始位置偏差的影响程度较大, 对测深精度和惯性导航系统提出了相对较高的要求; 该算法地形适应性较强, 但丰富地形更有利于匹配导航; 通过合理地选择应用参数, 可有效降低匹配误差, 提高导航性能。该项研究可为日后匹配算法在水下导航工程实践中的应用提供参考。Abstract: Aiming at the problem that the performance of underwater terrain aided navigation is affected by many factors so that best performance cannot be obtained, an underwater digital map with corresponding resolution is made via bilinear interpolation method, and the point-mass filter(PMF) algorithm based on direct probability criterion is adopted to simulate the effects such as speed, depth error, heading error, speed error, initial positional deviation, and underwater topographical features on the navigation performance for undersea vehicle. And the application performance of the PMF algorithm under complex conditions is analyzed. Simulation results show that: 1) the PMF matching algorithm has strong stability under complex conditions; 2) within a certain range, the algorithm shows better resistance to speed and heading errors, but the matching performance will seriously degrade if the speed is too low; 3) the algorithm is greatly affected by the depth error and the initial position deviation, and it needs relatively high requirements for sounding accuracy and inertial navigation system; 4) the algorithm has strong terrain adaptability, and rich terrain is more conducive to matching navigation; and 5) proper selection of the application parameters can effectively reduce the matching error and improve the navigation performance.
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