Particle filter initialization in non-linear non-Gaussian radar target tracking

When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.

Velocity measurement technique for high-speed targets based on digital fine spectral line tracking

Target vdocity and acceleration are two of the most important features for identification of warheads and decoys in ballistic missile defense phased array radar systems. Velocity compensation is also the necessary step for one-dimensional range profile imaging. According to the high-vdocity characteristics of ballistic objects and the low data rate of phased array radars with multiple target tracking, a fine spectral line digital velocity tracking frame is presented and a new method is developed to extract velocity error and resolve the velocity ambiguity in the measurement loop. Simulation results demonstrate the effectiveness of the proposed technique.

Texture invariant estimation of equivalent number of looks based on log-cumulants in polarimetric radar imagery

A novel estimation of the equivalent number of looks (ENL) is proposed in statistical modeling of multilook polarimetric synthetic aperture radar (PolSAR) images for the product model, which is based on the log-determinant moments (LDM). The LDM estimators discovered by looking at certain log-cumulants of the intensities of different polarization channels and the multilook polarimetric covariance matrix, which can be used for both the Gaussian model and all product models. This estimator has analytic expressions, and uses the full covariance matrix and intensities as input, which makes more statistical information available. Experiments based on simulated data and real data are performed. The comparisons among the widely used methods of equivalent number of looks (ENL) estimation for the product model such as K and G0 distributions show that the performance of the LDM estimator is outstanding. The performance of estimators for the real data of San Francisco and Flevoland is analyzed and the results are according to those of simulated data. Finally, it can be concluded that the LDM estimator is well robust to each product model with low computational complexity and high accuracy. ? 1990-2011 Beijing Institute of Aerospace Information.

Best linear unbiased estimation algorithm with Doppler measurements in spherical coordinates

In an active radar-tracking system,the target-motion model is usually modeled in the Cartesian coordinates,while the radar measurement usually is obtained in polar/spherical coordinates.Therefore the target-tracking problem in the Cartesian coordinates becomes a nonlinear state estimation problem.A number of measurement-conversion techniques,which are based on position measurements,are widely used such that the Kalman filter can be used in the Cartesian coordinates.However,they have fundamental limitations to result in filtering performance degradation.In fact,in addition to position measurements,the Doppler measurement or range rate,containing information of target velocity,has the potential capability to improve the tracking performance.A filter is proposed that can use converted Doppler measurements（i.e.the product of the range measurements and Doppler measurements） in the Cartesian coordinates.The novel filter is theoretically optimal in the rule of the best linear unbiased estimation among all linear unbiased filters in the Cartesian coordinates,and is free of the fundamental limitations of the measurement-conversion approach.Based on simulation experiments,an approximate,recursive implementation of the novel filter is compared with those obtained by four state-of-the-art conversion techniques recently.Simulation results demonstrate the effectiveness of the proposed filter.

Causes, effects and control of seasonal frost action in railways

Seasonally cold climate and resulting frost action set great demands to railway track substructure in order to maintain Irack geomelry. Chal- lenges culminate on high-speed lines, where the tolerances for roughness are the tightest. Problems may result in highly increased Irack maintenance and need for temporary speed reslrictions. The causes of frost action can be associated with subsoil, subballast or ballast. The major concern in frost protection is to avoid the freezing of frost susceptible subsoil by using sufficient thickness of subballast and relying on non-fi＇ost-susctible subballast material. This paper provides an overview of the main research findings on the role of ballast, subballast and subsoil in frost acedon. In new comlruclion the material specificalions, design procedures and construction methods have been developed to ensure adequate performance of Irack subscatt, but special challenges exist in managing existing Wacks that were not designed for modem requirements. In order to perform cost-effective and sustainable track maintenance, it is necessary to recognize the problem areas and define the root-causes of problems. For locating the problem sections and defining the causes of defects, a sophisticated analysis based on integration of track geometry and ground penetrating radar （GPR） data has been developed and is summarized in this paper,

Trajectory Estimation with Multi-range-rate System Based on Sparse Representation and Spline Model Optimization

The classic state methods for trajectory estimation in boost phase with multi-range-rate system include method of point-by-point manner and that of spline-model-based manner. Both are deficient in terms of model-approximation accuracy and systematic error determination thus resulting in the estimation errors well beyond the requirements, especially, concerning the maneuvering trajectory. This article proposes a new high-precision estimation approach based on the residual error analysis. The residual error comprises three components, i. e. systematic error, model truncation error and random error. The approach realizes self-adaptive estimation of systematic errors in measurements following the theory of sparse representation of signals to minimize the low-frequency components of residual errors. By taking median- and high-frequency components as indexes, the spline model-approximation is improved by optimizing node sequence of the spline function and the weight selection for data fusion through iteration. Simulation has validated the performances of the proposed method.