Hongqi Fan

Impact of Mode Decision Delay on Estimation Error for Maneuvering Target Interception

For highly maneuvering target interception in terminal guidance, state estimation error is characterized. First, the estimators state space model is constructed with a stochastic linear hybrid system (SLHS) in the presence of the unknown lateral acceleration of the evader. If the mode switches of SLHS are observable, the mode decision-maker can correctly identify the mode (or discrete state) sequence with a known delay, called mode decision delay. Then, the dynamics of continuous-state estimation error is constructed analytically given the mode decision delay. To achieve the guaranteed performance, the upper bound of mode decision delay and the lower bound of mode sojourn time are found. Finally, the results are corroborated through a simulation of the typical heading-on interception scenario. The conclusions in this paper are directive to the design and performance analysis of SLHS estimator.

Analysis of Quantum Radar Cross Section and Its Influence on Target Detection Performance

Quantum radar is a new detection technology based on the mechanism of quantum physics and is promising for enhancing radar target detection capability. In this letter, the quantum radar equation is established based on the traditional radar equation; meanwhile, how the quantum radar cross section (QRCS) influences target detection performance and how QRCSs for some typical targets distribute are investigated via simulations. Simulation results demonstrate that the signal-to-noise ratio increases with the QRCS, the peak values of side-lobes of the QRCS for the cylinder surface fluctuate little, and the QRCS for corner reflectors almost exhibits no variations in a wide range of incident angles. The results listed above can benefit the signal design and performance evaluation of quantum radar as well as the design of quantum stealthy targets.

Joint multi-target filtering and track maintenance using improved labeled particle PHD filter

As is known, the most prominent advantage of Finite Set Statistics (FISST) based multi-target tracking algorithms is it could cope with complicated tracking problems arising from special events such as target birth, target death and tracks crossing without complicated data association. Through improving the existing labeled particle Probability Hypothesis Density (L-P-PHD) filter, an improved labeled particle PHD (IL-P-PHD) filter is proposed in this paper. Simulation experiment shows that the tracking performance of IL-P-PHD filter is much better than L-P-PHD filter on complicated multi-target tracking problems, IL-P-PHD filter could extract target track information while efficiently detecting target birth and disappearance and stably estimating target state.

Target Turning Maneuver Detection using High Resolution Doppler Profile

Target turning maneuvering is always accompanied with the rapid attitude variations, which are helpful to achieve high cross-range resolution for pulsed coherent radar. Thus, it is feasible to detect target turning maneuver using the high resolution Doppler profile (HRDP). The preliminaries concerning the HRDP are first introduced, including its formulation, extraction requirements, and procedure. The principle of turning maneuver detection using the HRDP is then fully explored. A novel detector is developed based on the back propagation (BP) neural network. Two novel indices for performance evaluation are proposed. Finally, a simulation environment with software tools capable of generating target dynamic echoes with realistic features is developed. The simulation results demonstrate that the proposed detector performs better than the other three up-to-date feature-based detectors as a whole.

Feature Aided Switching Model Set Approach for Maneuvering Target Tracking

Feature aided maneuver detector is popular for its low detection delay and high detection probability in decision-based single- model maneuvering target tracking (MTT) algorithms. We propose a switching model-set approach based on the feature aided maneuver detector for MTT. The flltering error dynamics in terms of detection delay are presented and a upper bound for detection delay with given standard Kalman flltering errors is accessed. Subsequently, a feature aided maneuver detector is introduced to enhance detection performance, and the flltering algorithm is proposed, including detailed flltering steps and computational formulae. Simulation results show that the proposed algorithm outperforms the popular autonomous multiple model (AMM) and interacting MM (IMM) algorithms.

Joint Design of Transmitted Sequence and Receiving Filter in the Presence of Doppler Shifts

In this paper, we study the joint design of transmitted sequence and receiving filter to improve the performance of radar in the presence of Doppler shifts. The mean-square error (MSE) of the estimates of the scattering coefficients of the point-like targets is considered to be the figure of merit. The design problem is cast as a joint optimization problem to minimize the MSE in the presence of target and clutter Doppler shifts. To tackle the design problem, we devise a new data model with respect to the Doppler shifts and propose a cyclic iterative approach to obtain optimized pairs for receiving filters and transmitted sequences. The proposed approach is based on fractional programming and iterations of the power method, and this approach is computationally efficient. Moreover, this approach can handle unimodularity constraints, quantization constraints, and peak-to-average power ratio constraints on the transmitted sequence. Simulation examples show the effectiveness of the proposed approach.

Imaging targets moving in formation using parametric compensation

When conventional motion compensation algorithms that are fit for a single target are applied to cooperative targets imaging, a well-focused image cannot be obtained due to the low correlation between adjacent returned signals. In this paper, a parametric compensation method is proposed for the imaging of cooperative targets. First, the problem of the imaging is formulated by analyzing the translational motion of the target moving along a rectilinear fight path and by assuming a signal model of cooperative targets imaging. A bulk image is then obtained by parametric compensation of the linear and quadratic phase terms, which is performed by means of estimating the translational motion parameters through the fractional Fourier transform. Next, the number of targets in the bulk image is estimated by clustering number estimation, and the segmented images from the bulk image are separated by the normalized cuts. Finally, well-focused images are obtained by refined parametric compensation of the residual quadratic and cubic phase terms, which is carried out by estimating the parameters through maximizing the image contrast. Simulation results demonstrate the effectiveness of the proposed method.

Bernoulli filter for range and Doppler ambiguous radar

A pulse Doppler radar worked in medium or high pulse repetition frequency (PRF) may suffer from range and Doppler ambiguities. The common method to solve ambiguities is to use multiple PRFs and do correlation between them. The ghosting problem may be caused by the false alarms in the correlation. When the signal-to-noise ratio is low, a low detection threshold is needed to guarantee the probability of detection, which may create a large amount of false alarms that are intractable for existing techniques. This study uses a Bayesian method to detect and track a single target in a range and Doppler ambiguous radar. The authors’ method is formulated based on the finite set representation of the target state and the recently developed Bernoulli filter. Besides, a sequential Monte Carlo implementation of the Bernoulli filter is proposed for the problem of range and Doppler ambiguous measurement. Simulation results show that the proposed filter can simultaneously detect and track the target using the ambiguous measurements in the presence of dense false alarms.

ISAR imaging of multiple moving targets using signals separation

The conventional motion compensation algorithms, which are designed for a single moving target, cannot be directly used to multiple targets ISAR imaging because the returned signals of these targets are overlapped in time and have low correlation. In this paper, a separated ISAR imaging method is proposed for multiple moving targets with uniformly accelerative rectilinear motion in the same radar beam. The second-order keystone transform (SKT) is used to correct range curvature for all targets without knowing their accelerations. Then the chirp rates of the signals of different targets are estimated by the Gauss Short-time Fractional Fourier transform (GSFrFT). The chirp rates of targets are different from each other. Then the returned signals of each individual target are separated based on its chirp rate in the fractional Fourier domain. Finally, after signals separation, the well-focused ISAR image of each individual target is obtained by the conventional motion compensation algorithm. Simulation results are presented to demonstrate the effectiveness of the proposed method.

State estimation performance of tracking system with range rate measurements

Digital signal processing techniques employed in modern radar systems enable the generation of measurements consisting of target 3D position and range rate. However, two crucial issues on range rate measurements utilization remain unresolved, that is, under what conditions and to what extent the performance improvement can be attained by incorporating range rate measurements into the tracking filter. This paper aims to address the two problems. Firstly, the state space models of tracking systems without and with range rate measurements are formulated. Secondly, the lower bounds, i.e., Posterior Cramér-Rao Bounds (PCRBs), for target state estimation errors of the two tracking systems are derived. Thirdly, the primary parameters relevant to the PCRB are discussed, and an effective method for analyzing their effects on state estimation is proposed by comparing the PCRBs of the two tracking systems. Finally, an application example is presented under a typical tracking scenario. The method and results will be of great interest for persons developing tracking system with range rate measurements.