MIMO radar: An idea whose time has come (original) (raw)

Evaluation of transmit diversity in MIMO-radar direction finding

Signal Processing, …, 2007

It has been recently shown that multiple-input multiple-output (MIMO) antenna systems have the potential to dramatically improve the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, the target's radar cross section (RCS) fluctuations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it provides measures to overcome those degradations or even utilizes the RCS fluctuations for new applications. This paper explores how transmit diversity can improve the direction finding performance of a radar utilizing an antenna array at the receiver. To harness diversity, the transmit antennas have to be widely separated, while for direction finding, the receive antennas have to be closely spaced. The analysis is carried out by evaluating several Cramer Rao bounds for bearing estimation and the mean square error (MSE) of the maximum likelihood estimate.

A MIMO radar system approach to target tracking

2009

In this paper, tracking performance of MIMO radar systems with distributed antennas and non-coherent processing is studied. The Bayesian Cramer-Rao bound (BCRB) on target location and velocity tracking is derived and the effect of the radars geometric layout and the target location on tracking accuracies is analyzed. The impact of the number of radars on the estimation errors is examined and the contribution of the target reflectivity and path loss to tracking performance is evaluated.

Predicted Detection Performance of MIMO Radar

IEEE Signal Processing Letters, 2000

It has been shown that multiple-input multiple-output (MIMO) radar systems can improve target detection performance significantly by exploiting the spatial diversity gain. We introduce the system model in which the radar target is composed of a finite number of small scatterers and derive the formula to evaluate the theoretical probability of detection for the system having an arbitrary array-target configuration. The results can be used to predict the detection performance of the actual MIMO radar without time-consuming simulations.

The Effect of Radar Cross Section and Speed of Target on the Detection of MIMO Radar

2018

In this paper, we address the problem of Direction of Departure (DOD) and Direction of Arrival (DOA) estimation for Multiple Input Multiple Output (MIMO) radar. The work presented studies the effect of Radar Cross Section (RCS), Signal to Noise Ratio (SNR) and speed of targets on the performance of the MIMO radar. Analysis can be used to find the direction of multiple types of targets such as CAPON, MUSIC and parallel factor (PARAFAC). To differentiate the meaning of targets, varying targets of different types, such as bicycle, bird, man, ship and jet have been considered. After defining suitable values for each type of target in 2D space, the performance of each type is discussed by using the MATLAB program. KeywordsMIMO Radar; Target Localization; Parallel Factor (PARAFC); Direction of Arrival.

High Resolution Capabilities of MIMO Radar

2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006

Multiple-input multiple-output (MIMO) radar is a multistatic architecture composed of multiple transmitters and receivers, which seeks to exploit the spatial diversity of radar backscatter. In conjunction with centralized processing, MIMO radar has the potential to significantly improve radar functions such as detection and parameter estimation. MIMO radar is distinct from other types of array radars such as phased array or STAP, which process the signals of closely spaced elements and, hence, cannot capitalize on the spatial characteristics of targets. In this work, we explore the ability of MIMO radar and coherent processing to locate a target with high resolution and to resolve targets located in the same range cell. A distributed target model is developed. It is demonstrated that MIMO radar with centralized coherent processing is able to resolve scatterers with a range resolution well beyond that supported by the signal bandwidth. The location estimation capabilities are further illustrated by introducing a new two-dimensional ambiguity function. The analysis is discussed in the context of established results for randomly thinned arrays. The investigation of high resolution MIMO radar also includes comparison with the performance of non-coherent MIMO radar and the effect on performance of the number of sensors and their locations.

Target tracking in MIMO radar systems: Techniques and performance analysis

2010

In this paper, moving target tracking performance in multiple input multiple output (MIMO) radar systems with distributed antennas and non-coherent processing is studied. Due to the use of multiple, widely distributed antennas, MIMO radar architectures support both centralized and decentralized tracking techniques. Each receiving radar may contribute to central processing by providing either raw data or partially/fully processed data. Estimation performance of centralized and decentralized tracking is analyzed through the Bayesian Cramer-Rao bound (BCRB). The BCRB offers insight into the effect of the radars geometric layout, the target location, and propagation path losses on tracking accuracies. It is shown that, with different propagation path loss, the manner in which decentralized estimations are combined in the fusion center effects the overall estimation performance. Two tracking algorithms are proposed, corresponding to respectively, a centralized and decentralized modes of operation. It is demonstrated that communication requirements and processing load may be reduced at a relatively low performance cost. Based on mission needs, the system may use either approach: centralized for high accuracy or decentralized for resource-aware tracking.

Direction finding for MIMO radar with colocated antennas using transmit beamspace preprocessing

2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009

The problem of direction finding for multiple targets in mono-static multiple-input multiple-output (MIMO) radar systems is considered. Assuming that the targets are located within a certain spatial sector, we focus the energy of multiple (two or more) transmitted orthogonal waveforms within that spatial sector using appropriately designed transmit beamforming. The transmit beamformers are designed so that matchfiltering the received data to the waveforms yields multiple (two or more) data sets with rotational invariance property that allows applying search-free direction finding techniques such as ESPRIT. Unlike previously reported MIMO radar ESPRITbased direction finding techniques, our method is applicable to arbitrary arrays and achieves better estimation performance at lower computational cost.

Non-coherent MIMO radar for target estimation: More antennas means better performance

2009 43rd Annual Conference on Information Sciences and Systems, 2009

This paper presents an analysis of the joint estimation of target location and velocity using multiple-input multiple-output (MIMO) radar. A theorem is formulated on the asymptotic properties of the maximum likelihood (ML) estimate The joint Cramer-Rao bound (CRB) is calculated for a Rayleigh fluctuating extended target. The mean square error (MSE) of the ML estimate is analyzed for orthogonal Gaussian pulses. It is shown that the signal to noise ratio (SNR) boundary between low and high MSE values can be lowered by increasing the number of antennas. The non-coherent MIMO radar ambiguity function (AF) is developed and illustrated by examples. It is shown that the product of the number of transmit and receive antennas can control the sidelobes level of the AF.