Research On Algorithm For The Localization Based On TOA In Wirelesss Sensor Network

In recent years, wireless sensor network is developed rapidily, and applicated gradually in military, medical treatment, environmental monitoring, bionomics research, etc.. Its key technology is the node localization. IR-UWB has the characteristic of fine time resolution, which can be applied to high precision node localization, so it is widely applied to the physical layer technology for WSN. The content of this dissertation is focus on the research of node localization technologies for IR-UWB wireless sensor network.At first, the dissertation introduces the concept and advantage of IR-UWB wireless sensor networks, and discusses the research status of localization technology. Then the advantage and disadvatage of the current ranging methods were analyzed, which include Angle Of Arrival (AOA), Received Signal Strength Indication (RSSI), Time Different Of Arrival (TDOA) and Time Of Arrival (TOA). Then according to the analyse results, the ranging algorithm which is suitable for the localization of IR-UWB wireless sensor network is discovered.This dissertation emphases on node location.The first step is ranging, so a dynamic threshold algorithm is proposed based on TOA estimation. The most of the current TOA methods are based on the static threshold algorithm, and cannot estimate the results for any signal to noise ratio. The other methods are based on a dynamic threshold algorithm that can estimate the result for any signal to noise ratio. But these methods only analyze the signals amplitude, and ignore the time delay, so statistic is imperfective and estimation error is large. To remove these disadvantages, this chapter proposes a optimal dynamic threshold algorithm based on TOA estimation. Firstly, the energy block which contains the direct path (DP) is detected by using the energy detection algorithm. Then according to the joint of the kurtosis, the mean excess delay spread and the root mean square delay spread, the optimal threshold value is extracted, the dynamic threshold formula is fitted, the location of DP is further estimated, and the TOA value is calculated. At last, to verify the merit of this algorithm, a simulation is carried out to compare the algorithm with other two ones.NLOS error is the main factor that effects localization. So the second step of node localization researches the identification and error mitigation of Line of Sight (LOS) and Non-Line of Sight (NLOS). At present, the corresponding researches focus mainly on cellular environment, the nodes of which are moving. The researches of this chapter focus mainly on WSN, the nodes of which are static. Firstly, the parameters:kurtosis, root mean square delay spread and skewness are obtained based on the multipath channel statistics. Then similar to the idea of joint likelihood ratio test, the obtained three parameters are jointed to identify LOS or NLOS. The proposed method is proved to be more precise than current methods by comparison. Moreover, in order to mitigate the NLOS errors, this chapter proposes a four segments weighted method based on current three segments weighted method. The chapter 5 will calculate the node coordinate by using this four segments weighted method to revise the ranging result of TOA.The last step analyzes the current methods for node localization, and proposes a method of network cooperative localization based on the analysis results. The forth segment weighted Least Squares (WLS) algorithm uses the information of TOA and NLOS to estimate the coordinate of the unknown nodes. Several simulations are carried out to prove that the proposed localization algorithm has less error and higher precision than three segment WLS algorithm, and the network cooperative localization is effective.