Quantized Kalman Filter for Sensor Networks with Random Packet Dropouts
Na Liu, Jing Ma, Shuli Sun · Advanced materials research · 2011
Based on the projection theory and the uniform quantization method, a quantized Kalman filter is presented for sensor networks with random packet dropouts from sensors to the fusion center (filter). The bandwidths are scheduled by the optimality index that energy consumption is minimized under a given performance constraint. Compared with the filter without quantization, the quantized filter given can reduce the energy consumption and has an effective tracking performance. A simulation example demonstrates the effectiveness of the proposed algorithm.