Guolong Cui

MIMO Radar Waveform Design With Constant Modulus and Similarity Constraints

We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations.

Coherent Integration for Maneuvering Target Detection Based on Radon-Lv’s Distribution

This letter considers the coherent integration problem for a maneuvering target, involving range migration (RM) and Doppler frequency migration (DFM) within one coherent pulse interval. A new coherent integration method, known as Radon-Lvs distribution (RLVD), is proposed. It can not only eliminate the RM effect via jointly searching in the targets motion parameters space, but also remove the DFM and achieve the coherent integration via Lvs distribution (LVD). Finally, several simulations are provided to demonstrate the effectiveness. The results show that for detection ability, the proposed method is superior to the moving target detection (MTD), Radon-Fourier transform (RFT), and Radon-fractional Fourier transform (RFRFT) under low signal-to-noise-ratio (SNR) environment.

A Fast Maneuvering Target Motion Parameters Estimation Algorithm Based on ACCF

This letter considers the motion parameters estimation problem for a maneuvering target with arbitrary parameterized motion. The slant range of the target is modeled as a polynomial function in terms of its multiple motion parameters and a fast estimation method based on adjacent cross correlation function (ACCF) is proposed, where the iterative adjacent cross correlation operation is employed to remove the range migration and reduce the order of Doppler frequency migration. Then the motion parameters are estimated via Fourier transform. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can estimate the parameters without searching procedure and acquire close estimation performance at high signal-to-noise ratio (SNR) with a much lower computational cost. Finally, simulations are provided to demonstrate the effectiveness.

Coherent Integration Algorithm for a Maneuvering Target With High-Order Range Migration

This paper considers the coherent integration problem for a maneuvering target with complex motions, where the velocity, acceleration, and jerk result in respectively the first-order range migration (FRM), second-order range migration (SRM), and third-order range migration (TRM) within the coherent pulse interval. A new coherent integration algorithm based on generalized keystone transform (KT) and second-order dechirp process is proposed, which employs the third-order KT, six-order KT, second-order KT, and fold factor searching to correct the TRM, SRM, and FRM, respectively. The range migration change during each step and computational complexity are also theoretically analyzed. Compared with the generalized Radon Fourier transform (GRFT) algorithm, the presented method can avoid the blind speed sidelobe (BSSL) and acquire close integration performance but with much lower computational cost. Simulations are provided to demonstrate the effectiveness. Finally, a generalized method, named generalized KT and generalized dechirp process (GKTGDP), is also introduced for the maneuvering target with arbitrary high-order range migration.

Performance Prediction of the Incoherent Radar Detector for Correlated Generalized Swerling-Chi Fluctuating Targets

We deal with the performance prediction of the incoherent radar receiver in the presence of arbitrary correlated, possibly nonidentically-distributed target backscattered echoes. The problem is of interest in some common scenarios that account for frequency agility, and polarization, as well as for spatial diversity. We develop analytic expressions for the detection probability in terms of function series, assuming that a generalized Swerling-chi distribution models the first order probability density function (pdf) of the target amplitude. Moreover, we study the speed of convergence of the resulting series and assess the impact on the detection performance of both the correlation and the nonidentical distribution of the target returns.

A Back-projection algorithm to stepped-frequency synthetic aperture through-the-wall radar imaging

Back-projection imaging algorithm is widely used in through-the-wall and GPR imaging because of the high image quality and being compensated easily. In this paper, the author introduce the back-projection algorithm to the stepped-frequency through-the-wall radar and put forward the time-minimization method to eliminate the walls effects, such as refraction, changing in speed and attenuation. Proof of concept is provided using real data collected in a laboratory environment. The results show that the BP algorithm can outputs a high quality image and the time-minimization method can eliminate the walls effect very well.

Signal detection with noisy reference for passive sensing

In many detection applications, the signal to be detected, referred to as target signal, is not directly available. A reference channel (RC) is often deployed to collect a noise-contaminated version of the target signal to serve as a reference, which is then used to assist detecting the presence/absence of the target signal in a test channel (TC). A standard approach is to cross-correlate (CC) the signals received in the TC and RC, respectively. When the signal-to-noise ratio (SNR) in the RC is high, the CC behaves like the optimum matched filter. However, when the SNR in the RC is low, the CC detector suffers significant degradation. This paper considers the above detection problem with a noisy reference signal. We propose four detectors based on the generalized likelihood ratio test principle, by treating the unknown target signal to be deterministic or stochastic and under conditions whether the noise variance is known or unknown. Our results demonstrate that the noise in the RC has an impact on the achievable detection performance. However, when the reference signal is noisy, three of the proposed detectors offer substantial improvements in detection performance over the CC detector. HighlightsExamined the problem of signal detection with a noisy reference signal.Proposed 4 new signal detectors by taking into account the noisy nature of the reference signal.Considered cases when the noise variance is known or unknown and when the signal to be detected is modeled as deterministic or random.Proposed techniques are shown to outperform the conventional cross-correlation based detector which ignores the noise in the reference signal.

Adaptive Transmit and Receive Beamforming for Interference Mitigation

We consider adaptive transmit and receive beampattern design for array radar systems. While adaptive processing is primarily employed for only receive beamforming in conventional design, we propose a fully adaptive approach involving jointly selecting the transmit correlation matrix and receive beamformer by maximizing the signal-to-interference-plus-noise ratio (SINR). The motivation of utilizing adaptive processing at the transmitter is that with imprecise knowledge of the interference (e.g., due to limited training data), only relying on adaptive receive beamforming may be inadequate for effective interference cancellation, whereas joint adaptive transmit and receive beamforming can afford a stronger ability to handle the interference. Simulations are provided to demonstrate the performance of the proposed joint beamforming approach.

Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar

This paper deals with the design of multiple-input multiple-output radar space-time transmit code (STTC) and space-time receive filter (STRF) to enhance moving targets detection in the presence of signal-dependent interferences. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to interference plus noise ratio (SINR) accounting for both a similarity constraint and a constant modulus requirement on the probing waveform. Each iteration of the algorithm involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problems, that can be globally solved in polynomial time via the Dinkelbacks procedure, are settled. The computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. In particular, the proposed technique provides a monotonic SINR improvement without limitations on the size of the similarity constraint and ensures convergence to a stationary point filling these important gaps in the open literature. Besides, the reported results highlight that the new devised procedure outperforms both in the optimized SINR value and the computational complexity than the available counterparts.

Fast Non-Searching Method for Maneuvering Target Detection and Motion Parameters Estimation

This paper considers the coherent integration problem for maneuvering target detection and motion parameters estimation, involving range migration (RM) and Doppler frequency migration (DFM) within the coherent pulse interval. A fast non-searching method based on adjacent cross correlation function (ACCF) and Lvs distribution (LVD) is proposed, where the adjacent correlation operation is first employed to remove the RM and reduce the order of DFM. After that, LVD is applied to realize the coherent integration, target detection and parameters estimation. In addition, at the cost of some performance loss, another fast method via ACCF iteratively is also introduced to further reduce the computational complexity and obtain the motion parameters estimation. The proposed two methods are fast in that they can be easily implemented by using complex multiplications, the fast Fourier transform (FFT) and inverse FFT (IFFT). Compared with the existing methods, the presented algorithms can obtain the motion parameters estimation without any searching procedure and can achieve a good balance between the computational cost and the detection ability as well as parameters estimation performance. Finally, several simulation experiments are provided to demonstrate the effectiveness.