A decentralized fusion estimator using linear coding compensation method with non-fixed dropout rates
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摘要:
为解决无线信道非固定丢包率建模和丢包补偿问题，研究了具有非固定丢包率的网络化多传感器融合估计问题。假定无线信道丢包率是非固定的，利用对过去得到的有限个测量值进行线性编码的方法对丢包进行补偿，针对系统矩阵中存在的非高斯非白噪声随机干扰，首先设计了一种利用每一时刻数据包到达变量的局部最优估计器，其次推导出融合估计误差协方差与传感器传输概率之间的函数关系。最后通过算例仿真验证所提方法的有效性。
Abstract:The networked multi-sensor fusion estimation problem is investigated in the paper for a class of networked system with non-fixed packet loss rates, which aims to solving the problem of modeling of non-fixed packet loss rates in wireless channel and the problem of dropout compensation. The dropout rate of the wireless channel is assumed to be non-fixed. A linear coding method is used at the sensor by combining the past several measurements to get a new measurement, which compensates the data. First, a recursive locally optimal estimator is designed by minimizing the mean square error accounting for the non-Gaussian non-white noise random disturbance of the system matrix and making good use of the real-time arrival information based on the received measurement. Second, the functional relationship between the fusion estimation error covariance and sensor transmitting probability is derived. Finally, simulation example is given to confirm the effectiveness of the proposed method.
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图 2 真实状态、融合及局部最优估计值计算结果
Figure 2. Calculation results of true state, fusion andlocally optimal estimates
图 3 估计误差协方差矩阵的迹计算结果
Figure 3. Calculation results of trace of estimationerror covariance matrixes
图 5 乘性噪声与融合估计精度的关系
Figure 5. Relationship between multiplicative noise and fusion estimation accuracy
表 1 不同传输概率下的融合估计精度
Table 1. Fusion estimation accuracy with different transmission rates
pk, tran* Tr(P200o) {0.06, 0.999, 0.999} 0.7077 {1, 1, 1} 0.7130 {0.9, 0.9, 0.9} 0.7152 {0.5, 0.5, 0.5} 0.7244 
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