TY - JOUR

T1 - Noncoherent MIMO radar for location and velocity estimation

T2 - More antennas means better performance

AU - He, Qian

AU - Blum, Rick S.

AU - Haimovich, Alexander M.

N1 - Funding Information:
Manuscript received June 03, 2009; accepted February 10, 2010. Date of publication March 01, 2010; date of current version June 16, 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Ljubisa Stankovic. Q. He and R. S. Blum were supported by the Air Force Research Laboratory under Agreement FA9550-09-1-0576, the National Science Foundation under Grant CCF-0829958, the U.S. Army Research Office under Grant W911NF-08-1-0449, and by the China Scholarship Council. A. M. Haimovich was supported in part by the U.S. Air Force Office of Scientific Research under Agreement FA9550-09-1-0303.

PY - 2010/7

Y1 - 2010/7

N2 - This paper presents an analysis of the joint estimation of target location and velocity using a multiple-input multiple-output (MIMO) radar employing noncoherent processing for a complex Gaussian extended target. A MIMO radar with M transmit and $N$ receive antennas is considered. To provide insight, we focus on a simplified case first, assuming orthogonal waveforms, temporally and spatially white noise-plus-clutter, and independent reflection coefficients. Under these simplifying assumptions, the maximum-likelihood (ML) estimate is analyzed, and a theorem demonstrating the asymptotic consistency, large MN, of the ML estimate is provided. Numerical investigations, given later, indicate similar behavior for some reasonable cases violating the simplifying assumptions. In these initial investigations, we study unconstrained systems, in terms of complexity and energy, where each added transmit antenna employs a fixed energy so that the total transmitted energy is allowed to increase as we increase the number of transmit antennas. Following this, we also look at constrained systems, where the total system energy and complexity are fixed. To approximate systems of fixed complexity in an abstract way, we restrict the total number of antennas employed to be fixed. Here, we show numerical examples which indicate a preference for receive antennas, similar to MIMO communications, but where systems with multiple transmit antennas yield the smallest possible mean-square error (MSE). The joint CramrRao bound (CRB) is calculated and the MSE of the ML estimate is analyzed. It is shown for some specific numerical examples that the signal-to-clutter-plus-noise ratio (SCNR) threshold, indicating the SCNRs above which the MSE of the ML estimate is reasonably close to the CRB, can be lowered by increasing MN. The noncoherent MIMO radar ambiguity function (AF) is developed in two different ways and illustrated by examples. It is shown for some specific examples that the size of the product MN controls the levels of the sidelobes of the AF.

AB - This paper presents an analysis of the joint estimation of target location and velocity using a multiple-input multiple-output (MIMO) radar employing noncoherent processing for a complex Gaussian extended target. A MIMO radar with M transmit and $N$ receive antennas is considered. To provide insight, we focus on a simplified case first, assuming orthogonal waveforms, temporally and spatially white noise-plus-clutter, and independent reflection coefficients. Under these simplifying assumptions, the maximum-likelihood (ML) estimate is analyzed, and a theorem demonstrating the asymptotic consistency, large MN, of the ML estimate is provided. Numerical investigations, given later, indicate similar behavior for some reasonable cases violating the simplifying assumptions. In these initial investigations, we study unconstrained systems, in terms of complexity and energy, where each added transmit antenna employs a fixed energy so that the total transmitted energy is allowed to increase as we increase the number of transmit antennas. Following this, we also look at constrained systems, where the total system energy and complexity are fixed. To approximate systems of fixed complexity in an abstract way, we restrict the total number of antennas employed to be fixed. Here, we show numerical examples which indicate a preference for receive antennas, similar to MIMO communications, but where systems with multiple transmit antennas yield the smallest possible mean-square error (MSE). The joint CramrRao bound (CRB) is calculated and the MSE of the ML estimate is analyzed. It is shown for some specific numerical examples that the signal-to-clutter-plus-noise ratio (SCNR) threshold, indicating the SCNRs above which the MSE of the ML estimate is reasonably close to the CRB, can be lowered by increasing MN. The noncoherent MIMO radar ambiguity function (AF) is developed in two different ways and illustrated by examples. It is shown for some specific examples that the size of the product MN controls the levels of the sidelobes of the AF.

KW - Ambiguity function (AF)

KW - Cramér-Rao bound (CRB)

KW - Joint estimation

KW - Mean-square error (MSE)

KW - Noncoherent MIMO radar

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U2 - 10.1109/TSP.2010.2044613

DO - 10.1109/TSP.2010.2044613

M3 - Article

AN - SCOPUS:77953788491

VL - 58

SP - 3661

EP - 3680

JO - IEEE Transactions on Acoustics, Speech, and Signal Processing

JF - IEEE Transactions on Acoustics, Speech, and Signal Processing

SN - 1053-587X

IS - 7

M1 - 5422709

ER -