Target Detection and Parameter Estimation for MIMO Radar Systems

Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL
IEEE Transactions on Aerospace and Electronic Systems (Impact Factor: 1.76). 08/2008; 44(3):927 - 939. DOI: 10.1109/TAES.2008.4655353
Source: IEEE Xplore


We investigate several target detection and parameter estimation techniques for a multiple-input multiple-output (MIMO) radar system. By transmitting independent waveforms via different antennas, the echoes due to targets at different locations are linearly independent of each other, which allows the direct application of many data-dependent beamforming techniques to achieve high resolution and excellent interference rejection capability. In the absence of array steering vector errors, we discuss the application of several existing data-dependent beamforming algorithms including Capon, APES (amplitude and phase estimation) and CAPES (combined Capon and APES), and then propose an alternative estimation procedure, referred to as the combined Capon and approximate maximum likelihood (CAML) method. Via several numerical examples, we show that the proposed CAML method can provide excellent estimation accuracy of both target locations and target amplitudes. In the presence of array steering vector errors, we apply the robust Capon beamformer (RCB) and doubly constrained robust Capon beamformer (DCRCB) approaches to the MIMO radar system to achieve accurate parameter estimation and superior interference and jamming suppression performance.

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    • "In light of (59) and the analysis in Section V.A, the GLRT in [30] is also CFAR. Moreover, the GLRT in (59) is statistically equivalent to the random variable f in (41). "
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    ABSTRACT: For colocated MIMO radar target detection in colored noise, we propose two adaptive detectors according to the Rao and Wald test criteria. These detectors do not need training data and possess constant false alarm rate properties. We investigate the manner how they work. From a detection viewpoint we show that there is no need of matched filtering for colocated MIMO radar. We derive the statistical distributions of the proposed detectors, and then obtain the analytical expressions for the probabilities of false alarm and detection both for deterministic and random signals. Numerical examples are provided to compare the detection performance of the Rao and Wald tests with an existing detector.
    Full-text · Article · Oct 2015 · IEEE Transactions on Aerospace and Electronic Systems
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    • "Subject to the current technical conditions, the monostatic colocated MIMO radar is the most practical MIMO radar system [6]. The possible advantages of the colocated MIMO radars have provided the motivation to explore their capability in various contexts such as target detection [7], target localization [5], target tracking [8], waveform design [9], [10], and antenna allocation [11]. Due to the unique structure of the colocated MIMO radar, various desired beam patterns can be generated by multiple colocated transmitters [9], [10], [12]. "
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    ABSTRACT: A colocated multiple-input multiple-output (MIMO) radar system has the ability to address multiple beam information. However, the simultaneous multibeam working mode has two finite working resources: the number of beams and the total transmit power of the multiple beams. In this scenario, a resource allocation strategy for the multibeam working mode with the task of tracking multiple targets is developed in this paper. The basis of our technique is to adjust the number of beams and their directions and the transmit power of each beam through feedback, with the purpose of improving the worst tracking performance among the multiple targets. The Bayesian Cramér–Rao lower bound (BCRLB) provides us with a lower bound on the estimated mean square error (MSE) of the target state. Hence, it is derived and utilized as an optimization criterion for the resource allocation scheme. We prove that the resulting resource optimization problem is nonconvex but can be reformulated as a set of convex problems. Therefore, optimal solutions can be obtained easily, which greatly aids real-time resource management. Numerical results show that the worst case tracking accuracy can be efficiently improved by the proposed simultaneous multibeam resource allocation (SMRA) algorithm.
    Full-text · Article · Jun 2015 · IEEE Transactions on Signal Processing
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    • "The latter is known as monostatic MIMO radar or bistatic MIMO radar [2, 6–10], where the transmitting and receiving antennas are closely spaced. Monostatic or bistatic MIMO radar, which can form receiving beam and virtual transmitting beam jointly at the receiver [2], has many advantages, such as narrower beamwidth, lower sidelobes, higher angular resolution, and higher angular estimation accuracy [6] [11]. And this paper focuses on the bistatic MIMO radar. "
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    ABSTRACT: The beamspace unitary ESPRIT (B-UESPRIT) algorithm for estimating the joint direction of arrival (DOA) and the direction of departure (DOD) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The conjugate centrosymmetrized DFT matrix is utilized to retain the rotational invariance structure in the beamspace transformation for both the receiving array and the transmitting array. Then the real-valued unitary ESPRIT algorithm is used to estimate DODs and DOAs which have been paired automatically. The proposed algorithm does not require peak searching, presents low complexity, and provides a significant better performance compared to some existing methods, such as the element-space ESPRIT (E-ESPRIT) algorithm and the beamspace ESPRIT (B-ESPRIT) algorithm for bistatic MIMO radar. Simulation results are conducted to show these conclusions.
    Full-text · Article · May 2015 · International Journal of Antennas and Propagation
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