Bistatic Multiple-input Multiple-output Radar System Research Articles

Space‐time adaptive detection for bistatic MIMO system under covariance matrix persymmetry and symmetric spectrum

Space-time adaptive detection (STAD) is an important research aspect of the bistatic multiple-input multiple-output (MIMO) radar system. The signal and clutter space-time models of the bistatic MIMO radar are described in this study. The knowledge-aided (KA) transform, which utilises the structural properties of the target-free data and the sample covariance matrix, is applied to increase the independent secondary data fourfold in the STAD frame. The performance assessment of the KA–STAD detectors with generalised likelihood ratio test (GLRT), adaptive matched filter (AMF), and Rao rules is presented. The simulation experiments show that the detection and constant false alarm rate performances of the presented KA–GLRT, KA–AMF, and KA–Rao detectors outperform the GLRT, AMF, and Rao detectors for the bistatic MIMO radar system STAD frame in clutter background with limited secondary data.

Joint DOD and DOA Estimation for Coherently Distributed Sources in Bistatic MIMO Radar Based on Joint Diagonalization

In this paper, an efficient method via unitary joint diagonalization is proposed to deal with the coherently distributed sources in bistatic multiple-input multiple-output (MIMO) radar systems. In order to determine the direction of departure (DOD) and direction of arrival (DOA) of the coherently distributed source, a special array configuration is designed both for transmitter and receiver in bistatic MIMO radar system. Then, a new signal model can be obtained by utilizing the designed array characteristic and the rotational invariance relationship is constructed both for DOD and DOA. For the special rotational invariance relationship, the joint diagonalization technique is adopted to locate the coherently distributed sources and the angular parameters are automatically paired without multidimensional search process. The proposed joint diagonalization method can also determine the targets when multiple imping sources have the common DODs or DOAs. Finally, the approximate determined Cramer-Rao bound of the proposed estimator for the coherently distributed sources is also derived. And, additional numerical results are conducted to verify the effectiveness and superiority of the proposed method.

Joint DOD and DOA estimation for bistatic multiple‐input multiple‐output radar target discrimination based on improved unitary ESPRIT method

Target position estimation of radar system has attracted much attention. Researchers have proposed a variety of joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation algorithms over the last few decades for this well-known problem. However, traditional estimation algorithms require a pairing process between the DOD and DOA estimation. In this study, the authors propose an improved unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm for joint DOD and DOA estimation without a pairing operation. The waveforms are transmitted by an array with M sensors and received by two detached sub-arrays with and sensors, respectively. Specifically, the proposed algorithm eliminates a pairing process via sharing the eigenvectors of DOD and DOA. Theoretical derivation demonstrates that the proposed algorithm requires less computational complexity than two-dimensional multiple signal classification (MUSIC), reduced-dimension MUSIC, and ESPRIT. Simulation results show that the proposed algorithm can effectively enhance the accuracy of identifying and locating targets for the bistatic multiple-input multiple-output radar system.

A Novel Method for Doppler and DODDOA Jointly Estimation Based on FRFT in Bistatic MIMO Radar System

This paper studies the problem of parameter estimation jointly in bistatic Multiple-Input Multiple-Output (MIMO) radar system. For moving target, the echo often contains time-varied Doppler frequency. Thus, this paper proposes a new signal model and a novel method for parameter estimation in bistatic MIMO radar system. Firstly, an extended signal model is presented in bistatic MIMO radar. Secondly, two Doppler parameters are jointly estimated by searching the peak of the fractional correlation function. Finally, MUSIC algorithm and ESPRIT algorithm are used to estimate DODs and DOAs. Simulation results are presented to verity the effectiveness of the proposed method.

Parameter Estimation Based on Fractional Power Spectrum Density in Bistatic MIMO Radar System Under Impulsive Noise Environment

This paper takes an Alpha-stable distribution as the noise model to solve the parameter estimation problem of bistatic multiple-input multiple-output (MIMO) radar system in the impulsive noise environment. For a moving target, its echo often contains a time-varying Doppler frequency. Furthermore, the echo signal may be corrupted by a non-Gaussian noise. It causes the conventional algorithms and signal models degenerating severely in this case. Thus, this paper proposes a new signal model and a novel method for parameter estimation in bistatic MIMO radar system in the impulsive noise environment. It combines the fractional lower-order statistics (FLOS) and fractional power spectrum density (FPSD), for suppressing the impulse noise and estimating parameters of the target in fractional Fourier transform domain. Firstly, a new signal array model is constructed based on the $$\alpha $$ź-stable distribution model. Secondly, Doppler parameters are jointly estimated by peak searching of the FLOS---FPSD. Furthermore, two modified algorithms are proposed for the estimation of direction-of-departure and direction-of-arrival (DOA), including the fractional power spectrum density based on MUSIC algorithm (FLOS---FPSD---MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS---FPSD---ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method.

Parameter Estimation Based on Fractional Correlation under Alpha-Stable Distribution Noise Environment in Bistatic MIMO Radar System

This paper takes the-stable distribution as the noise model and works on the parameter estimation problem of bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment.This paper presents a signal model and a novel method for parameter estimation in bistatic MIMO radar system in the impulsive noise environment. Firstly, a signal array model is constructed based on the-stable distribution model. Secondly, Doppler parameters are jointly estimated by searching the optimal rotation angle to meet concentrated-energy of the FLOS-FC. Furthermore, two algorithms are presented for the estimation of DODs and DOAs, including based on FLOS-MUSIC algorithm and FLOS-ESPRIT algorithm. Simulation results are presented to verity the effectiveness of the proposed method.

Joint parameter estimation and target localization for bistatic MIMO radar system in impulsive noise

This paper presents a novel method for joint parameter estimation of multiple targets for bistatic multiple-input multiple-output radar system in impulsive noise. Firstly, a new signal array model is constructed according to a 3-D motion characteristics of target in impulsive noise environment. Secondly, Doppler frequency parameters are jointly estimated by peak searching of a fractional lower-order ambiguity function based on fractional Fourier transform (FLOS-FAF) and a dechirping method. Furthermore, two modified algorithms are proposed for the estimation of direction-of-departure and direction-of-arrival, including the MUSIC algorithm based on the fractional lower-order ambiguity function (FF-MUSIC) and the ESPRIT algorithm based on the fractional lower-order ambiguity function (FF-ESPRIT) in the fractional Fourier transform domain. Simulation results are presented to verify the effectiveness of the proposed method.

互耦条件下双基地MIMO雷达的收发角度估计

The presence of mutual coupling between elements is known to significantly degrade the performance of the multi-target localization algorithm for a bistatic multiple input multiple output (MIMO) radar system. By using the banded symmetric Toeplitz matrices for the transmit and receive arrays, we propose an ESPRIT-based algorithm to estimate the Direction Of Departure (DOD) and Direction Of Arrival (DOA) for a bistatic MIMO radar system in the presence of unknown mutual coupling. An improved automatic pairing is presented to avoid the invalidation of the existing pairing method when identical DOD/DOA exist in one dimension. Simulation results show that the proposed method can localize the multi-target efficiently in the presence of identical DOD/DOA in one dimension without the spectrum search and extra pairing. Compared with the MUSIC-like algorithm, the proposed method is more robust in dealing with a number of mutual coupling coefficients, and the perturbation matrix errors. The estimation accuracy of the proposed method is better than that of the MUSIC-like algorithm.

Parameter estimation based on fractional power spectrum under alpha-stable distribution noise environment in wideband bistatic MIMO radar system

This paper takes the alpha-stable distribution as the noise model and works on the parameter estimation problem of wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. Furthermore, the echo signal may be corrupted by the non-Gaussian noise. The conventional algorithms degenerate severely in the impulsive noise environment. Thus, this paper proposes a new wideband signal model and a novel method in wideband bistatic MIMO radar system. It combines the fractional lower order statistics and fractional power spectrum, for suppressing the impulse noise and estimating parameters of the target. Firstly, a new signal array model is proposed under the alpha-stable distribution noise model. Secondly, Doppler stretch and time delay are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of the direction-of-departure and direction-of-arrival, including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method.

A novel joint parameter estimation method based on fractional ambiguity function in bistatic multiple-input multiple-output radar system

Due to the three dimensional motion characteristics of the target, the received scattering signal often contains a cubic term in its phase function. The existing signal model is not appropriate to approximate parameters in this case. In this paper, we propose a new signal model to accurately estimate parameters of the target. We use a novel approach, the fractional ambiguity function, to estimate Doppler frequency parameters in the fractional Fourier transform domain. Furthermore, we also develop two sub-array models to accurately estimate the direction-of-departure and direction-of-arrival by employing the proposed fractional cross-ambiguity function based MUSIC (FCAF-MUSIC) algorithm and the fractional cross-ambiguity function based ESPRIT (FCAF-ESPRIT) algorithm. Simulation results are presented to verify the effectiveness of the proposed method.

Antenna Geometry Conditions for MIMO Radar With Uncoupled Direction Estimation

We mainly focus on the role played by the antenna geometry in the direction estimation performance for a direction finding (DF) bistatic multiple-input multiple-output (MIMO) radar. First, we introduce the signal and the noise models which satisfy the space-time separability conditions. Then, we derive an expression of the Cramer-Rao lower bound (CRLB) on target parameters with the antenna locations for a single point target in the far-field scenario. We show that, under the space-time separability conditions, the temporal dimension parameters (range and range rate) and spatial dimension parameters [direction-of-departure (DOD) and the direction-of-arrival (DOA)] are uncoupled. We also show that DOD and DOA are uncoupled because of their spatial independence. In addition, we derive a set of the necessary and sufficient geometrical constraints for the uncoupled direction estimation which is based on the diagonal Fisher information matrix (FIM). We present that, when both the transmit and the receive antenna location parameters have equivalent auto-moment-of-inertia tensors of x and y axes, and zero cross-moment-of-inertia tensors of x, y and z axes, the bistatic MIMO radar system with uncoupled direction estimation can be obtained. The corresponding conditions are extended to monostatic MIMO radar case for their commonness of the colocated antenna geometry. In numerical example section, we show several representative antenna geometries to illustrate the antenna geometry conditions derived in this paper.