Performance Analysis of Single-Step Localization Method Based on Matrix Eigen-Perturbation Theory with System Errors

Direct position determination (DPD) is a novel technique in passive localization field recently, receiving superior localization performance compared with the conventional two-step method. The DPD estimator using Doppler shifts is first proposed by Weiss, but it is not suitable for antenna arrays. Additionally, the performance analysis of this method with system errors is absent. This study discusses the single-step localization problem based on moving arrays and exhibits the performance analysis via matrix eigen-perturbation theory with system errors. First, the DPD method using angle of arrival and Doppler shifts is introduced. Then, by adding the eigenvalue perturbations to the estimated Hermitian matrix, the asymptotic linear formulation of localization errors is derived. Consequently, the mean square error of the DPD method is available. Finally, Cramér–Rao bound without system errors is presented, providing a benchmark for the best localization precision and revealing the influence of system errors on the localization precision. Simulation results demonstrate the theoretical analysis in this study.

ZigBee Node Locating Technology Based on Genetic Algorithm

Location technology as Wireless Sensor Network’s support technology for most applications has been widely researched, ZigBee is one of representative technology of WSN. On the basis of the common two-step localization algorithm, this paper proposes a locating method that optimize the measurement data using genetic algorithm before locating calculation, then using multilateral measurement least-square method for calculating position. Experimental results show that the modified algorithm is significantly reduced the position error, effectively improve the position accuracy.

A New Method for Vertical Deformation Detection Using Survey Control Networks

Usually, the Survey control networks are used for deformation detection in a specific area using observations taken at different epochs. Where the coordinates obtained from two epochs, using least squares technique, are compared in order to assess if a deformation of a specified magnitude exists. Traditionally, the global congruency test is carried out so as to detect if the area of the network has undergone any movement (uplift or subsidence) due to natural or manmade causes. As a next step, localization methods are used to determine deformations at specific points in case there are changes in shape. In this research a new method is developed to establish deformations at specific points directly. The method is tested using a vertical control network simulated at various epochs of observation. The results obtained are compared with those obtained by another used method. Results obtained using this method indicate that vertical deformations greater than 0.03m using a precision of observation less than 10 can be detected at a minimum significant level of 0.05 (95% confidence level).