Splitting the Linear Least Squares Problem for Precise Localization in Geosensor Networks
Splitting the Linear Least Squares Problem for Precise Localization in Geosensor Networks
复制标题
分解线性最小二乘问题以实现地理传感器网络的精确定位
DOI：
10.1007/11863939_21
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
R. Bill
中科院分区：
文献类型：
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作者：
F. Reichenbach;A. Born;D. Timmermann;R. Bill
大量廉价且易于部署的无线传感器能够对城市环境和荒凉地形进行区域范围的监测。由于这些传感器节点的随机部署，其中一个关键问题是他们的位置确定。噪声距离测量和高度有限的资源，每个传感器节点，由于微小的硬件和小电池容量，需要发展强大的，能量感知，和精确的定位算法。我们相信这可以通过适当地分配复杂的定位任务之间的所有参与节点。因此，我们使用线性化工具将所产生的非线性方程组线性化为可以通过分布式最小二乘法求解的线性形式。它表明，在本文中，我们可以节省这种新的方法超过47%的计算成本，同时保持低的网络流量。此外，我们描述了内存优化处理复杂的矩阵运算，只有几个字节的传感器节点上的内存。
Large amounts of cheap and easily deployable wireless sensors enable area-wide monitoring of both urban environments and inhospitable terrain. Due to the random deployment of these sensor nodes, one of the key issues is their position determination. Noisy distance measurements and the highly limited resources of every sensor node, due to tiny hardware and small battery capacity, demand the development of robust, energy aware, and precise localization algorithms.We believe this can be achieved by appropriately distributing the complex localization task between all participating nodes. Therefore, we use a linearization tool to linearize the arising non-linear system of equations into a linear form that can be solved by a distributed least squares method. It is shown in this paper that we can save with this new approach more than 47% of computation cost whilst maintaining a low network traffic. Additionally, we describe memory optimizations to process the complex matrix operations with only a few kilobyte of memory on the sensor node.