The Research Of Wireless Sensor Network Location Technology Based On Jackknife Correction

In recent years, Wireless sensor networks are widely used in military, industrial automation, new agriculture, intelligent transportation, smart home, intelligent detection, environmental protection and other fields as a new technology. In wireless sensor networks, sensor nodes transmit their collected data to the users. In many applications, it is crucial to get the location information corresponding to the data, which is involved in the location technology of WSN. As an important supporting technology, the researchers both at home and abroad pay close attention to the location technology of wireless sensor networks.Based on the previous research on wireless sensor network node localization algorithm, this paper proposes a new method of measuring error correction:JKC (JackKnife Correction).This correction method was used respectively based on the distance and angle of the lateral positioning algorithm, proposes two positioning actuarial method. Positioning actuarial algorithm based on distance correction:JKDC (JackKnife Distance Correction), In the process of localization, the least square method is used in the preliminary positioning, correct the distance between the beacon and the unknown node use JKC correction method, finally using the least square method according to the revised final location and distance measurement.Positioning of the actuarial method based on the angle correction:JKAC (JackKnife Angle Correction), with the help of rotation directional antenna, measure the azimuth Angle of the unknown node to anchor nodes,the AOA algorithm is used in the preliminary positioning, correct the angle between the beacon and the unknown node use JKC correction method, finally location is according to the adjusted Angle.In the study of this paper, use JKC algorithm to modify the obtained distance and angle information, reducing the positioning error from the source, thus realizing location refinement. Simulation and experiment is used for verification of the effectiveness of the algorithm.