目前無線感測網路定位法已發展成兩大類：range-free與range-based定位演算法。range-free為不需要任何測距技術而使用參考節點間的連結度來估算為數眾多的未知節點位置。Range-based定位則需使用一些測距技術，如TOA、TDOA、AOA和RSSI等當作測量鄰居節點距離的工具，並藉由這些測量資訊計算未知節點位置。為了增加錨節點的覆蓋率問題,一些基於測距為基礎的無線感測網路定位法使用疊代式的多邊測量可以解決錨節點不足的影響，但是卻有兩個缺點,一是某些節點仍然存在錨節點鄰居節點不足的情形,其二會有誤差累積的影響等缺點。因此，在本文中我們提出基於PSO最佳化演算法使用未知節點的最接近鄰居測距來估算未知節點位置，藉由這個方法減緩誤差累積的影響以及增加孤立節點成功定位的機會。由電腦模擬的結果中，新的定位法相較其他定位方法對於不同環境因素影響下也能有效定位。 Localization in wireless sensor networks has developed two categories: range-free and range-based localization algorithms. The range-free algorithms don''t need any range techniques but use connectivity among the anchors to estimate the positions of unknown nodes. The range-based algorithms must need some range techniques such as TOA, TDOA, AOA and RSSI to measure the neighbors'' distance. And use these measurements to estimate the position of the unknown nodes. In order to add the coverage of anchor nodes, some range-based localization algorithms use iterative multilateration to solve low density problem of the anchor nodes. But the iterative multilateration algorithm suffers two drawbacks: first, some nodes still don''t have sufficient anchor nodes in their neighborhood; second, the use of localized unknown nodes as anchor nodes can bring the cumulative error. Therefore, we propose a PSO based localization algorithm using the distance of the closest neighbor to estimate the unknown node''s location. We use this algorithm to reduce the error accumulation effects and add the probability of the orphan nodes which can successfully calculate the locations. Compared with some localization algorithms, new method can be more effective performance for different environment in our computer simulations.
