Optimal waveform precoder design for narrowband MIMO radar systems (original) (raw)
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Optimalwaveform design for MIMO radarwith low probability of interception
2011 17th International Conference on Digital Signal Processing (DSP), 2011
In this paper, we consider the waveform design problem of multiple input multiple output (MIMO) radar in the presence of an interceptor. By the joint considerations of high estimation accuracy and low probability of interception, we formulate the problem as maximizing the mutual information with a constraint on the Kullback-Liebler (KL) divergence. Then it is converted effectively to a convex optimization, which can be solved efficiently to give the optimal waveform. Simulation results show that there exits the optimal tradeoff between the estimation accuracy and the probability of interception.
MIMO radar waveform design based on mutual information and minimum mean-square error estimation
IEEE Transactions on Aerospace and Electronic Systems, 2000
This paper addresses the problem of radar waveform design for target identification and classification. Both the ordinary radar with a single transmitter and receiver and the recently proposed multiple-input multiple-output (MIMO) radar are considered. A random target impulse response is used to model the scattering characteristics of the extended (nonpoint) target, and two radar waveform design problems with constraints on waveform power have been investigated. The first one is to design waveforms that maximize the conditional mutual information (MI) between the random target impulse response and the reflected waveforms given the knowledge of transmitted waveforms. The second one is to find transmitted waveforms that minimize the mean-square error (MSE) in estimating the target impulse response. Our analysis indicates that under the same total power constraint, these two criteria lead to the same solution for a matrix which specifies the essential part of the optimum waveform design. The solution employs water-filling to allocate the limited power appropriately. We also present an asymptotic formulation which requires less knowledge of the statistical model of the target.
Waveform Design For MIMO Radar Systems
Iconic Research and Engineering Journals, 2020
Waveform design is critical to the realization of a Multiple Input Multiple Output (MIMO) radar system. If the wave forms being transmitted are perfectly orthogonal, the virtual array consists of more elements than the transmit array and this provides additional degrees of freedom which improves performance. The correlation properties of the wave forms transmitted determine the characteristics of the system. In this paper, a binary orthogonal waveform with low auto correlation and cross correlation properties is designed. Orthogonality in transmitted wave forms is required in MIMO radar systems to enable the use of match filtering at the outputs to separate the different transmit paths. Exploiting the orthogonality of the walsh hadamard matrix based on non identical walsh functions, the simulated annealing statistical optimization tool is used to obtain the orthogonal signal set with the desired low correlation properties.
MIMO Radar Waveform Design with Practical Constraints: A Low-Complexity Approach
2018 IEEE 18th International Conference on Communication Technology (ICCT)
In this letter, we consider the multiple-input multiple-output (MIMO) radar waveform design in the presence of signal-dependent clutters and additive white Gaussian noise. By imposing the constant modulus constraint (CMC) and waveform similarity constraint (SC), the signal-to-interference-plus-noise (SINR) maximization problem is non-convex and NP-hard in general, which can be transformed into a sequence of convex quadratically constrained quadratic programming (QCQP) subproblems. Aiming at solving each subproblem efficiently, we propose a low-complexity method termed Accelerated Gradient Projection (AGP). In contrast to the conventional IPM based method, our proposed algorithm achieves the same performance in terms of the receive SINR and the beampattern, while notably reduces computational complexity.
Adaptive Radar Waveform Design for Multiple Targets: Computational Aspects
2007
In this paper we describe the optimization of an information theoretic criterion for radar waveform design. The method is used to design radar waveforms suitable for simultaneously estimating and tracking parameters of multiple targets. Our approach generalizes the information theoretic water-lling approach of Bell. The paper has two main contributions. First, a new information theoretic design criterion for designing multiple waveforms under a joint power constraint when beamforming is used both at transmitter and receiver. Then we provide a highly ef cient algorithm for optimizing the transmitted waveforms, by approximating the information theoretic cost function. We show that using Lagrange relaxation the optimization problem can be decoupled into a parallel set of lowdimensional search problems at each frequency, with dimension de ned by the number of targets instead of the number of frequency bands used.
MIMO Radar Waveform Design With Constant Modulus and Similarity Constraints
IEEE Transactions on Signal Processing, 2014
We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations. Index Terms-Constant modulus and similarity constraints, MIMO radar, sequential optimization algorithms, waveform design. I. INTRODUCTION M ULTIPLE-INPUT Multiple-Output (MIMO) radar, unlike a standard phased-array radar emitting scaled versions of a single waveform, transmits multiple probing signals, which provides extra degrees of freedom in the design of the radar system as well as in developing more sophisticated signal processing algorithms [1]. According to the configuration of the antennas, the MIMO radar systems can be classified into two types. The first one [2], [3] employs widely separated transmit and receive antennas such that a target can be viewed from different spatial aspects, resulting in spatial diversity of the system. The spatial diversity can improve the performance of detection and angle estimation. The second one [4], [5] involves transmit and receive antennas that are colocated (spaced close enough).
SpringerPlus
Background Multiple input and multiple output systems (MIMO) radiate multiple probing signals through it their transmit antennas and receive multiple coded waveforms from multiple locations. MIMO radar systems have many advantages including high resolution target detection/estimation (Haimovich et al. 2008), significantly improved parameter identifiability (Li et al. 2007). The performance of the transmitted waveforms is judged by their correlation properties (Deng et al. 2004; Liu et al. 2007, 2008). The waveforms with good autocorrelation properties provide high range resolution and good crosscorrelation helps in multiple target return separability. So, there is a need to design MIMO radar waveforms as orthogonal pulses with low correlation properties. In literature, the orthogonal sequences are generated with low autocorrelation and crosscorrelation peak sidelobe levels using various algorithms. Deng et al. (2004) has proposed simulated annealing (SA) algorithm to optimize the frequency sequences for the development of the orthogonal discrete frequency coding waveforms frequency hopping (DFCW_FF) for netted radar systems. Liu has proposed orthogonal DFCW_FF (Liu et al. 2007) and orthogonal discrete frequency coding waveforms linear frequency modulation (DFCW_LFM) (Liu et al. 2008) using a modified genetic algorithm (MGA).
Transmits Beamforming Designmodel for Mimo Radar
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2013
This Paper describe the method of transmits beamforming design for MIMO radar. Transmit beamforming in MIMO radar based on the design of multiple correlated waveforms have been proposed.In this paper we present a different approach based on a reformulation of the problem which separates in a natural way the spatial and temporal parts of the design. This separation provides clearer insight into the transmit beamformer design and reveals the close connections to previous work on beam pattern synthesis and multi-rank beamformers. It also enables the application of well-known methods to the MIMO transmit beamformer design
Information Theoretic Adaptive Radar Waveform Design for Multiple Extended Targets
2007
Abstract—In this paper, we use an information theoretic approach to design radar waveforms suitable for simultaneously estimating and tracking parameters of multiple extended targets. Our approach generalizes the information theoretic water-filling approach of Bell to allow optimization for multiple targets simultaneously. Our paper has three main contributions. First, we present a new information theoretic design criterion for a single transmit waveform using a weighted linear sum of the mutual informations between target radar signatures and the corresponding received beams (given the transmitted waveforms). We provide a family of design criteria that weight the various targets according to priorities. Then, we generalize the information theoretic design criterion for designing multiple waveforms under a joint power constraint when beamforming is used both at the transmitter and the receiver. Finally, we provide a highly efficient algorithm for optimizing the transmitted waveforms...
IEEE Transactions on Signal Processing, 2017
In multiple-input multiple-out (MIMO) radar, for desired transmit beampatterns, appropriate correlated waveforms are designed. To design such waveforms, conventional MIMO radar methods use two steps. In the first step, the waveforms covariance matrix, R, is synthesized to achieve the desired beampattern. While in the second step, to realize the synthesized covariance matrix, actual waveforms are designed. Most of the existing methods use iterative algorithms to solve these constrained optimization problems. The computational complexity of these algorithms is very high, which makes them difficult to use in practice. In this paper, to achieve the desired beampattern, a low complexity discrete-Fourier-transform based closed-form covariance matrix design technique is introduced for a MIMO radar. The designed covariance matrix is then exploited to derive a novel closed-form algorithm to directly design the finite-alphabet constant-envelope waveforms for the desired beampattern. The proposed technique can be used to design waveforms for large antenna array to change the beampattern in real time. It is also shown that the number of transmitted symbols from each antenna depends on the beampattern and is less than the total number of transmit antenna elements.