Study on Mimo Arrays Optimization (original) (raw)

A design-algorithm for MIMO radar antenna setups with minimum redundancy

2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS 2013), 2013

Coherent multiple-input multiple-output (MIMO) radar systems with co-located antennas, form monostatic virtual arrays by discrete convolution of a bistatic setup of transmitters and receivers. Thereby, a trade-off between maximum array dimension, element spacing and hardware efforts exists. In terms of estimating the direction of arrival, the covariance matrix of the array element signals plays an important role. Here, minimum redundancy arrays aim at a hardware reduction with signal reconstruction by exploiting the Toeplitz characteristics of the covariance matrix. However, the discrete spatial convolution complicates the finding of an optimal antenna setup with minimum redundancy. Combinatorial effort is the consequence. This paper presents a possible simplified algorithm in order to find MIMO array setups of maximum dimension with minimum redundancy.

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.

Bistatic MIMO Radar System Design and the Effects of Antenna Placement on Parameter Estimation

2020

Date of publication (dd/mm/yyyy): 25/03/2020 Abstract – In this paper a bistatic Multiple Input Multiple Output (MIMO) ground based air surveillance radar system is designed for a maximum target range of 150 kilometers from the transmitter and 175 kilometers from the receiver, a range resolution of 7.5m, the overall detection rate is 90% and the False alarm rate ( FAR) = 1e-6. The radar operating frequency is 10 gigahertz. The design focuses on implementation of angle estimation and the effects of antenna placement on angle estimation performance. Most literatures on bistatic MIMO radar systems assume equal transmit and receive antenna elements with half wavelength inter element spacing for both arrays. An antenna placement scheme for varying the number of transmit and receive antenna for good angle estimation performance is proposed. Matlab simulations were performed to evaluate the performance of the proposed method.

Optimum Partitioning of a Phased-MIMO Radar Array Antenna

IEEE Antennas and Wireless Propagation Letters, 2017

In a Phased-Multiple-Input-Multiple-Output (Phased-MIMO) radar the transmit antenna array is divided into multiple sub-arrays that are allowed to be overlapped. In this paper a mathematical formula for optimum partitioning scheme is derived to determine the optimum division of an array into sub-arrays and number of elements in each sub-array. The main concept of this new scheme is to place the transmit beam pattern nulls at the diversity beam pattern peak side lobes and place the diversity beam pattern nulls at the transmit beam pattern peak side lobes. This is compared with other equal and unequal schemes. It is shown that the main advantage of this optimum partitioning scheme is the improvement of the main-to-side lobe levels without reduction in beam pattern directivity. Also signalto-noise ratio is improved using this optimum partitioning scheme.

Antenna allocation for MIMO radars with collocated antennas

2012

This paper deals with the antenna allocation problem in Multiple-Input Multiple-Output (MIMO) radar systems with collocated antennas. After deriving the Cramer-Rao Lower Bound (CRLB) as the cost function, the optimal distribution of antennas is found by applying the relevant operators to the CRLB. A convex optimization algorithm is then proposed to find the optimum distribution of antennas that achieves the optimal CRLB. It is also shown that the optimization problem can be simplified to the well-known Semi-definite Programming (SDP) for a single target scenario. Using a number of simulations, it is shown that the localization algorithm also leads to superior results when the optimal antenna configuration is used.

Target Characterization Using MIMO Radar

International Journal on Smart Sensing and Intelligent Systems, 2020

The exploitation of coherency gain and diversity gain to improve the MIMO system performance is a burning research topic. This paper is to examine the performance analysis of MIMO radar by utilizing the above-said gains. The authors have analyzed the performance of the MIMO radar, in terms of mathematical modeling, considering the probability of detection and post-processing SNR, with respect to changes in the diversity order. Furthermore, this paper also deals with the practical implementation and analysis of the said system, demonstrating the range imaging and RCS pattern of a known standard target.

Sparse Antenna Array Design for MIMO Radar Using Softmax Selection

2021

MIMO transmit arrays allow for flexible design of the transmit beampattern. However, the large number of elements required to achieve certain performance using uniform linear arrays (ULA) maybe be too costly. This motivated the need for thinned arrays by appropriately selecting a small number of elements so that the full array beampattern is preserved. In this paper we propose Learn-to-Select (L2S), a novel machine learning model for selecting antennas from a dense ULA employing a combination of multiple Softmax layers constrained by an orthogonalization criterion. The proposed approach can be efficiently scaled for larger problems as it avoids the combinatorial explosion of the selection problem. It also offers a flexible array design framework as the selection problem can be easily formulated for any metric.

A Modified Method for Beam-Forming Using Covariance Matrix in MIMO Radar System

International journal on engineering, science and technology, 2022

A MIMO radar provides solution for beamforming, since transmit beampattern synthesis is well proven method for stimulating the antenna array to develop the beampattern. It is close to the desired one which can give minimum error between these two. A covariance matrix in beamforming contains the direction of invariable data and magnitude distribution in multidimensional space which decides the closeness with the desired beampattern. Here, selection of an optimal covariance matrix is constrained optimization problem with minimization of cost function. In high directivity radar systems, the antenna beam is needed to be steered to cover a large area for detection. In this proposed work, minimization of convex function and transmit beampattern synthesis is carried out with modifications of the covariance matrix "R cov " for minimum and maximum transmission power utilization constraints. The beampattern design problem is reformulated here, as semi-definite programming optimization problem and solved using convex optimization, with MATLAB simulation platform. The results show that the beampattern generated using this modified covariance matrix is optimally close to desired pattern.