Xiang Jiabin

A new ISAR range alignment method based on particle swarm optimizer

The particle swarm optimizer algorithm (PSO) is a recently developed evolutionary search technique, In order to improve the precision of range alignment in ISAR data processing, a new method is presented based on particle swarm optimizer. The range profile distance is used as fitness function in PSO searching motion parameters, which evaluate each individual based on target range profiles, in such case the computational cost is strongly reduced. The experiment analysis on simulation data and the real ship data verify the effectiveness of the novel algorithm.

An approach of radar clutter recognition based on higher-order statistics combination

Radar clutter recognition is very useful for optimizing the processing and detection strategy of modern radar signal processing system to improve the performance of the processing system even the whole radar system to the maximum. A new radar clutter recognition approach based on higher-order statistics combination (HOSC) and its modification called weighed HOSC is presented, it can not only classify radar clutter, but also offer the corresponding parameters of the clutter. In comparison with other clutter recognition methods such as rectangular figure-based amplitude analysis, the proposed method is better. From the simulation results, it is seen that this clutter recognition approach has a higher recognition rate especially when the length of the clutter samples is short.

A fast range alignment approach for ISAR imaging based on minimum entropy criterion

The range alignment method of ISAR imaging based on the minimum entropy has heaven computational burden and needs long searching time. Aimed at the burden, under the same rule, a novel fast range alignment approach was proposed. The approach mainly makes use of the character that the synthesizing vector generated by two adjacent range echoes has different wave entropy at different time delay, thus the range alignment can be realized with varied step searching manner to reduce searching time and meet the requirement for real processing. The results of the real data processing show the validity of the proposed method.

Distributed adaptive OSWCA CFAR detector

In the sense of likelihood ratio test (LRT), a weighted adaptive OSWCA CFAR detector using distributed sensors is proposed in this paper. In the scheme, a local test statistic, which is the ratio of its test sample level and a designated order statistic (OS) of its reference samples, is calculated by each sensor, and then each sensor transmits its local test statistic to the fusion center. At the fusion center, the final decision is made based on weighted cell averaging algorithm (WCA). Since the weights are adjusted according to different signal-to-noise/clutter ratio (SNR), adaptively, the proposed detector can be available in the case of that the target echo and noise/clutter that have different level for each sensor. Unlike many current distributed CFAR detectors, which assuming that all noise/clutter samples satisfy independent identical distributed (IID) and have same SNR for each sensor. Meanwhile, for a Rayleigh fluctuating target in Gaussian noise of unknown level, we obtain its closed-form expressions for the false alarm probability and the detection probability. The numerical analysis results indicate that the proposed OSWCA scheme can be available.

Detection Performance Analysis of Distributed OSCA CFAR with Nonconherent Integration

A novel distributed detector, called order statistic cell-averaging (OSCA) detector, are proposed in the case of noncoherent integration, In this detector, each sensor transmits its test cell sample and a designated order statistic (OS) of its reference observations surrounding test cell to the fusion center. At the fusion center, the global noise power level is obtained with cell-averaging (CA) processing. Under the assumption of chi-square family target model and exponential clutter for independent square-law detector, the exact formulas of probability of false alarm (Pfa) and probability of detection (Pd), are derived. Finally, the corresponding detection performance is calculated with numerical analysis

Analysis and simulation of spatial interval non-uniform samples in azimuth multiple phase centers SAR

The problem of spatial interval non-uniform samples caused by mismatch between platform velocity and PRF is investigated. The relevant phase compensation expression is induced, and the simulation is given.

An Auto-adaptive Accumulation ISAR Imaging Algorithm Based on Time-frequency Analysis

Based on time-frequency analysis, an auto-adaptive accumulation ISAR imaging algorithm is proposed in this paper, which is especially suitable for complex motion target imaging. This new algorithm adaptively adjusts its accumulating scope by means of the echo correlation coefficient threshold and eliminates the strong interference cross-term by means of entropy principle. Validity of the proposed algorithm is verified by real ISAR data imaging

The method to inverse-simulate spaceborne MPC SAR data based on common airborne SAR data

This paper proposes a method to generate simulation data of spaceborne MPC SAR from real airborne complex image SAR data. This method can be used for testing the theoretical analysis result of spaceborne MPC SAR.

Research of simulation method by means of inversion from airborne SAR data to spaceborne MPC SAR data

A method to simulate spaceborne MFC SAR data is presented in this paper, and a simulation example of spaceborne system is given also.

A fully-digital processing approach for radar IF signal direct quadrature sampling

Based on a comparison study of the present methods for quadrature sampling of a radar IF signal, the sufficient-necessary condition for the sampling frequency choice is analyzed, and the choice range has been extended. Correspondingly, a new fully-digital approach for in-phase and quadrature components extraction is proposed.