基于测距的地面网络化弹药节点自定位算法

分析了极大似然估计算法中测距误差对定位误差的影响，提出了基于LMS（最小均方差）的自适应滤波原理的测距误差修正的自定位算法. 利用极大似然估计法初步估计节点位置，并得到定位误差信息，建立测距误差矩阵并更新网络中的滤波参数，完成对网络中测距误差的抑制，从而优化节点定信息. 实验仿真表明，优化处理使定位精度得到提高. 结果表明算法适用于锚节点密度较小的、低信噪比的网络化弹药系统.

Sequential Self-localization Algorithm of Networked Ammunitions Nodes

The affection of the distance-measuring error in localization was analyzed by using maximum likelihood estimation (MLE). A location algorithm based on LMS adaptive filter for error correction was proposed. The coordinators of the unknown nodes and location error information were obtained by using MLE. The distance-measuring error matrix was established and the parameters of the LMS adaptive filter were updated, which can restrain the distance-measuring error of the whole network, thus the location information of the unknown nodes was refined. The simulations show that after optimized by distance-measuring error matrix of pseudo anchor itself and the unknown nodes, the positional accuracy of network are improved compared to MLE. The algorithm proposed in this paper is applicable to self-localization of nodes in networked ammunitions system with low anchor node density and low SNR (signal-noise ratio).