The Improvement And Simulation Of DV-Hop Localization Algorithm In WSN

Self-localization technology for sensor nodes as one of the most important supporting technologies is of important research value in WSN. Sensor data has meaning only when it combines with location information in many applications. GPS positioning is disagree with wireless sensor network(WSN) for its high energy consumption and high-cost. So self-localization algorithms suitable for WSN are needed. Beside these, the accurate location information plays an important role in many applications. For example, the accurate location information can make target tracking more accurate.This paper focuses on the research of DV-Hop which is the most widely used at present. From the original DV-Hop algorithm, disadvantages of the original algorithm were analyzed, and the existing improved algorithms were summed up. An improved algorithm is proposed by analyzing the original DV-Hop algorithm's advantages and disadvantages, which is low cost, low error, extensible. The efficiency of the algorithm is verified by simulations in NS2, and the use value of the algorithm is analyzed.The improved algorithm is mainly the following three aspects:①The interior point test is proposed based on the anchor node. Because APIT algorithm can only be used for the situation of single jump and higher node density is needed. So it cannot be used for multiple hops algorithm. An inner point test is put forward which does not suffer hop and node density restriction of anchor node. The simulation results indicate that the interior point testing based on anchor node has higher accuracy than APIT algorithm which is about 20%.②An improved DV-Hop algorithm based on local area is proposed. The original DV-Hop uses global strategy which makes a larger hop-distance estimation error in random WSN. So the original DV-Hop has a lower location precision. Through the method of determining internal and external limit local positioning is realized. The key of local positioning is the anchor node choosing strategy, and the determination of internal and external restriction is based on the strategy. The strategy is that there are three anchor nodes in selected anchor nodes which can make the unknown node in the triangles constructed by them and using the node to calculate local hop-distance. Outer limit is determined by considering anchor node as unknown node to assess the local positioning scope of the entire network. the Anchor nodes taking part in positioning in outer limit range is determined by using anchor node choosing strategy, then the external restriction is determined.③Coverage statistic and bacon nodes seeding algorithm are added in the improved DV-Hop. The distribution of anchor nodes is assessed through the statistics of anchor node coverage, then adding anchor nodes to these areas which is lack of anchor node to satisfy the demands of coverage to make more reasonable distribution of anchor nodes, and ensure enough anchor nodes localization needed then ensure the positioning accuracy. In practice, according to the coverage of statistical results anchor nodes can be seeded by several times which will make more reasonable distribution of anchor node improving the utilization efficiency of anchor node and achieve the purpose that using a less anchor node get the localization accuracy required. Simulation results show that the improved algorithm on the basis of the original algorithm localization accuracy increased by 50%, and the improved algorithm has favorable adaptability and expansibility.