基于RSSI测距的加权概率定位算法

针对无线传感网络中每条链路衰减因子的不同,提出了一种基于RSSI测距的加权概率定位算法。该算法先将可能存在的未知节点区域划分成栅格,运用高斯噪声模拟路径衰减指数误差以构建信号传播概率模型,根据信号强度确定信标节点的权值。然后由概率模型和相应的权值赋予栅格不同的置信度,将置信度最大栅格的位置作为未知节点的坐标。最后根据网络的连通信息消除翻转歧义。实验表明,在相同的条件下,与MLS算法相比,该算法更接近真实环境,具有更高的定位精度。

Weighted probabilistic localization algorithm based on RSSI measurement

Concerning the problem that path loss exponent for each link is different , a weighted probabilistic localiza-tion algorithm is proposed based on RSSI.Firstly, the area where the unknown node may exist is divided into a num-ber of grids.Using Gaussian noise simulates path loss exponent error to construct the probability model of radio signal propagation, the beacon nodes’ weights are determined according to their signal strengths.Then, grids’ confidence degree is calculated according to probability models and beacon nodes’ weights, the coordinates of the grid which has greatest confidence degree as unknown node’s location.Finally, according to the network topology information elimi-nates flip ambiguity .The simulation experiments show that under the same conditions , compared with the MLS algo-rithm, the proposed algorithm is closer to the real environment and has higher positioning accuracy .