ISAR Signal Tracking and High-Resolution Imaging by Kalman Filtering

In a short observation time, after the range alignment and phase adjustment, the motion of a target can be approximated as a uniform rotation. The radar observing process can be simply described as multiplying an observation matrix on the ISAR image, which can be thought of as a linear system. It is known that the longer observation time is, the higher cross-range resolution is. In order to deal with the conflict between short observation time and high cross-range resolution, we introduce Kalman filtering (KF) into the ISAR imaging and propose a novel method to reconstruct a high-resolution image with short time observed data. As KF has excellent reconstruction performance, it leads to a good application in ISAR image reconstruction. At each observation aperture, the reconstructed image denotes the state vector in KF at the aperture time. It is corrected by a two-step KF process: prediction and update. As iteration continues, the state vector is gradually corrected to a well-focused high-resolution image. Thus, the proposed method can obtain a high-resolution image in a short observation time. Both simulated and real data are applied to demonstrate the performance of the proposed method.

A Fast Detection Algorithm for the X-Ray Pulsar Signal

The detection of the X-ray pulsar signal is important for the autonomous navigation system using X-ray pulsars. In the condition of short observation time and limited number of photons for detection, the noise does not obey the Gaussian distribution. This fact has been little considered extant. In this paper, the model of the X-ray pulsar signal is rebuilt as the nonhomogeneous Poisson distribution and, in the condition of a fixed false alarm rate, a fast detection algorithm based on maximizing the detection probability is proposed. Simulation results show the effectiveness of the proposed detection algorithm.

Static Network Code Dgps Positioning vs. Carrier Phase Single Baseline Solutions for Short Observation time and Medium-Long Distances

Static Network Code Dgps Positioning vs. Carrier Phase Single Baseline Solutions for Short Observation time and Medium-Long DistancesGPS land surveys are usually based on the results of processing GPS carrier phase data. Code or pseudorange observations due to considerations of accuracy requirements and robustness are preferred in navigation and some GIS applications. Generally, the accuracy of that positioning is in the range of about 1-2 meters or so, on average. But the main problem in code GPS positioning is to know how to estimate the real accuracy of DGPS positions. It is not such an easy process in code positioning when one reference station is used. In most commercial software, there are no values of accuracy but only positions are presented. DGPS positions without estimated errors cannot be used for surveying tasks and for most GIS applications due to the fact that every point has to be have accuracy determined. However, when we used static GPS positioning, it is well known that the accuracy is determined, both during baseline processing and next by the adjustment of a GPS network. These steps of validation with redundancy in classical static phase baseline solutions allow wide use of static or rapid static methods in the main land surveying tasks. Although these control steps are commonly used in many major surveying and engineering tasks, they are not always effective in terms of short-observation-time sessions. This paper presents a new network DGPS approach of positioning with the use of at least three reference stations. The approach concerns also valid accuracy estimation based on variance-covariance (VC) matrix in the least-squares (LS) calculations. The presented network DGPS approach has the ability of reliable accuracy estimation. Finally, network DGPS positioning is compared with static baselines solutions where five-min sessions were taken into consideration for two different rover stations. It was shown that in a short observation time of GPS positioning, code network DGPS results can give even centimetre accuracy and can be more reliable than static relative phase positioning where gross errors often happen.