Zhiyong Song

A new multiple extended target tracking algorithm using PHD filter

Abstract A new multiple extended target tracking algorithm using the probability hypothesis density (PHD) filter is proposed in our study, to solve problems on tracking performance degradation of the extended target PHD (ET-PHD) filter under the nonlinear conditions and its intolerable computational requirement. It is noted that with the current Gaussian mixture implement of ET-PHD filter satisfying tracking performance could only be obtained under linear and Gaussian conditions. To extend the application of ET-PHD filter for nonlinear models, our study has derived a particle implement of ET-PHD (ET-P-PHD) filter. Our study finds that the main factors influencing the computational complexity of the ET-P-PHD filter are the partition number of measurement set and the calculation of non-negative coefficients of cells in partitions. With the pretreatment of measurements and application of a new K -means clustering based measurement set partition method, we have successfully decreased the partition number. In addition, a gating method for target state space, which is based on likelihood relationship between target state and measurement, is proposed to simplify the calculation of non-negative coefficients. Simulation results show that the algorithms proposed by our study could satisfyingly deal with multiple extended target tracking issues under nonlinear conditions, and lead to significantly lower computational complexity with tiny effect on tracking performance.

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.

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.

Optimal OFDM waveform design for extended targets detection

In this paper, the problem of extended targets detection in signal-dependent interference based on orthogonal frequency division multiplexing (OFDM) waveform is addressed. Compared with other radar waveforms, OFDM has a thumbtack ambiguity function and the spectrum can be elaborately designed through changing the complex weights transmitted over different subcarriers. First, the optimal waveform design algorithm based on maximizing the signal-to-noise ratio (SNR) of the output receiver is introduced and the analytic expression of the waveform with optimal energy spectral density (ESD) is also derived. Then, combining the characteristic of OFDM waveform, a cycle iterative algorithm (CIA) based on fast Fourier transform (FFT) is proposed to search for the optimal solution of the objective function. Numerical examples show the ESD of designed waveform matches the optimal ESD well and the detection performance is also improved by optimizing the frequency weights of transmitted waveform.

A fast algorithm for designing the transmitted waveform and receive filter of MIMO radar

The authors study the problem of the transmitted waveform and the receiving filter design for multiple-input multiple-output (MIMO) radar in signal-dependent interference environment. The mean-square error of point target scattering coefficient estimate is considered to represent the measurement of the system. A fast computational approach is proposed to obtain optimal pairs for the transmitted waveform and receive filter. The proposed algorithm basing on fractional programming and power method-like iterations is efficient. Furthermore, this algorithm can address constant modulus constraint and peak-to-average-power ratio (PAR) constraint on the transmitted waveform. The effectiveness of this approach is demonstrated by numerical simulations.

Reducing the waveform autocorrelation and cross correlation for MIMO radar with multiple pulse train coding

Reducing the correlation level lies at the core of the waveform design for multiple-input multiple-output (MIMO) radar system. In this paper, a new approach to the design of waveform for MIMO radar is proposed. The multiple pulse train coding is employed and the compression accumulation is introduced. In this manner, the waveform correlation can be almost eliminated and the optimal compression accumulation results with low range sidelobe is obtained. Numerical simulations demonstrate that the performance of the proposed approach is superior to that of previous state-of-the-art algorithms.

Target Detection in Low Grazing Angle with Adaptive OFDM Radar

Multipath effect is the main factor of deteriorating target detection performance in low grazing angle scenario, which results from reflections on the ground/sea surface. Amplitudes of the received signals fluctuate acutely due to the random phase variations of reflected signals along different paths; thereby the performances of target detection and tracking are heavily influenced. This paper deals with target detection in low grazing angle scenario with orthogonal frequency division multiplexing (OFDM) radar. Realistic physical and statistical effects are incorporated into the multipath propagation model. By taking advantage of multipath propagation that provides spatial diversity of radar system and frequency diversity of OFDM waveform, we derive a detection method based on generalized likelihood ratio test (GLRT). Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. Simulation results show that the detection performance can be improved due to the multipath effect and adaptive OFDM waveform design.

Joint design of transmitted sequence and receive filter in clutter and interference

A new method for designing transmitted sequence and receive filter in the signal-dependent clutter and signal-independent interference environment is proposed. The mean-square error of point-like target scattering coefficient estimates is considered as the measurement of the radar system. Both the finite energy constraint and the similarity constraint are enforced for controlling certain characteristics of transmitted sequence. To tackle the design problem, we devise a new cyclic iterative approach to obtain optimized transmitted sequence and receive filter.