Transmit Energy Focusing for DOA Estimation in MIMO Radar with Colocated Antennas
Aboulnasr Hassanien, Sergiy A. Vorobyov
备注：
29 pages, 9 figures, submitted to IEEE Trans. Signal Processing in June 2010
发表信息：
A. Hassanien and S.A. Vorobyov, "Transmit energy focusing for DOA estimation in MIMO radar with colocated antennas," IEEE Trans. Signal Processing, vol. 59, no. 6, pp. 2669-2682, June 2011
In this paper, we propose a transmit beamspace energy focusing technique for multiple-input multiple-output (MIMO) radar with application to direction finding for multiple targets. The general angular directions of the targets are assumed to be located within a certain spatial sector. We focus the energy of multiple (two or more) transmitted orthogonal waveforms within that spatial sector using transmit beamformers which are designed to improve the signal-to-noise ratio (SNR) gain at each receive antenna. The subspace decomposition-based techniques such as MUSIC can then be used for direction finding for multiple targets. Moreover, the transmit beamformers can be designed so that matched-filtering 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 for two data sets or parallel factor analysis (PARAFAC) for more than two data sets. Unlike previously reported MIMO radar ESPRIT/PARAFAC-based direction finding techniques, our method achieves the rotational invariance property in a different manner combined also with the transmit energy focusing. As a result, it achieves better estimation performance at lower computational cost. Particularly, the proposed technique leads to lower Cramer-Rao bound than the existing techniques due to the transmit energy focusing capability. Simulation results also show the superiority of the proposed technique over the existing techniques.
In this paper, we propose a cyclic prefix (CP) based MIMO-OFDM range reconstruction method and its corresponding MIMO-OFDM waveform design for co-located MIMO radar systems. Our proposed MIMO-OFDM waveform design achieves the maximum signal-to-noise ratio (SNR) gain after the range reconstruction and its peak-to-average power ratio (PAPR) in the discrete time domain is also optimal, i.e., 0dB, when Zadoff-Chu sequences are used in the discrete frequency domain as the weighting coefficients for the subcarriers. We also investigate the performance when there are transmit and receive digital beam…
In this paper, colocated MIMO radar waveform design is considered by minimizing the integrated side-lobe level to obtain beam patterns with lower side-lobe levels than competing methods. First, a quadratic programming problem is formulated to design beam patterns by using the criteria for a minimal integrated side-lobe level. A theorem is derived that provides a closed-form analytical optimal solution that appears to be an extension of the Rayleigh quotient minimization for a possibly singular matrix in quadratic form. Such singularities are shown to occur in the problem of interest, but proof…
We consider a colocated MIMO radar scenario, in which the receive antennas forward their measurements to a fusion center. Based on the received data, the fusion center formulates a matrix which is then used for target parameter estimation. When the receive antennas sample the target returns at Nyquist rate, and assuming that there are more receive antennas than targets, the data matrix at the fusion center is low-rank. When each receive antenna sends to the fusion center only a small number of samples, along with the sample index, the receive data matrix has missing elements, corresponding to …
In this paper, we propose a two-dimensional (2D) joint transmit array interpolation and beamspace design for planar array mono-static multiple-input-multiple-output (MIMO) radar for direction-of-arrival (DOA) estimation via tensor modeling. Our underlying idea is to map the transmit array to a desired array and suppress the transmit power outside the spatial sector of interest. In doing so, the signal-tonoise ratio is improved at the receive array. Then, we fold the received data along each dimension into a tensorial structure and apply tensor-based methods to obtain DOA estimates. In addition…
We address the problem of tensor decomposition in application to direction-of-arrival (DOA) estimation for transmit beamspace (TB) multiple-input multiple-output (MIMO) radar. A general 4-order tensor model that enables computationally efficient DOA estimation is designed. Whereas other tensor decomposition-based methods treat all factor matrices as arbitrary, the essence of the proposed DOA estimation method is to fully exploit the Vandermonde structure of the factor matrices to take advantage of the shift-invariance between and within different subarrays. Specifically, the received signal of…
Recently, several array radar structures combined with sub-Nyquist techniques and corresponding algorithms have been extensively studied. Carrier frequency and direction-of-arrival (DOA) estimations of multiple narrow-band signals received by array radars at the sub-Nyquist rates are considered in this paper. We propose a new sub-Nyquist array radar architecture (a binary array radar separately connected to a multi-coset structure with M branches) and an efficient joint estimation algorithm which can match frequencies up with corresponding DOAs. We further come up with a delay pattern augmenti…
In order to improve the accuracy and resolution for transmit beamspace multiple-input multiple-output (MIMO) radar, a search-free direction-of-arrival (DOA) estimation method based on tensor decomposition and polynomial rooting is proposed. In the proposed method, a 3-order tensor is firstly designed to model the received signal of MIMO radar on the basis of the multi-linear property. Then, the factor matrix with target DOA information is obtained by the tensor decomposition via alternating least squares (ALS) algorithm, and subsequently the DOA estimation is converted into the independent min…
In this paper, we address the problem of transmit beamspace design for multiple-input multiple-output (MIMO) radar with colocated antennas in application to direction-of-arrival (DOA) estimation. A new method for designing the transmit beamspace matrix that enables the use of search-free DOA estimation techniques at the receiver is introduced. The essence of the proposed method is to design the transmit beamspace matrix based on minimizing the difference between a desired transmit beampattern and the actual one under the constraint of uniform power distribution across the transmit array elemen…
Multiple-input multiple-output (MIMO) radar systems have been shown to achieve superior resolution as compared to traditional radar systems with the same number of transmit and receive antennas. This paper considers a distributed MIMO radar scenario, in which each transmit element is a node in a wireless network, and investigates the use of compressive sampling for direction-of-arrival (DOA) estimation. According to the theory of compressive sampling, a signal that is sparse in some domain can be recovered based on far fewer samples than required by the Nyquist sampling theorem. The DOA of tar…
A distributed MIMO radar is considered, in which the transmit and receive antennas belong to nodes of a small scale wireless network. The transmit waveforms could be uncorrelated, or correlated in order to achieve a desirable beampattern. The concept of compressive sampling is employed at the receive nodes in order to perform direction of arrival (DOA) estimation. According to the theory of compressive sampling, a signal that is sparse in some domain can be recovered based on far fewer samples than required by the Nyquist sampling theorem. The DOAs of targets form a sparse vector in the angle …
In this paper, we introduce a novel algorithm that can dramatically reduce the number of antenna elements needed to accurately predict the direction of arrival (DOA) for multiple input multiple output (MIMO) radar. The new proposed algorithm predicts the received signal of a large antenna setup using reduced number of antenna by using coupled dictionary learning. Hence, this enables the MIMO radar to resolve more paths, which could not be resolved by the fewer antennas. Specifically, we overcome the problem of inaccurate DOA estimation due to a small virtual array setup. For example, we can us…
We present a cognitive prototype that demonstrates a colocated, frequency-division-multiplexed, multiple-input multiple-output (MIMO) radar which implements both temporal and spatial sub-Nyquist sampling. The signal is sampled and recovered via the Xampling framework. Cognition is due to the fact that the transmitter adapts its signal spectrum by emitting only those subbands that the receiver samples and processes. Real-time experiments demonstrate sub-Nyquist MIMO recovery of target scenes with 87.5% spatio-temporal bandwidth reduction and signal-to-noise-ratio of -10 dB.
We propose a new technique for multiple-input multiple-output (MIMO) radar with colocated antennas which we call phased-MIMO radar. The new technique enjoys the advantages of MIMO radar without sacrificing the main advantage of phased-array radar which is the coherent processing gain at the transmitting side. The essence of the proposed technique is to partition the transmitting array into a number of subarrays that are allowed to overlap. Then, each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. Coherent processing gain …
In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix should satisfy certain properties, e.g., a small coherence. Prior work in the literature often employs randomized placement algorithms which optimize the prior distribution of antenna locations. The performance of these algorithms is suboptimal, as they can be easily enhanced via expurgation. In this paper, we suggest an iterative antenna placement algorithm which determines the antenna locations deterministically. The p…
In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as measurement matrix. The samples are subsequently forwarded to a fusion center, where an L1-optimization problem is formulated and solved for target information. CS-based MIMO radar exploits the target sparsity in the angle-Doppler-range space and thus achieves the high localization performance of traditional MIMO radar but with many fewer measurements. The measurement matrix is vital for CS recovery performance. This …
Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction information of several electromagnetic waves/sources from the outputs of a number of receiving antennas that form a sensor array. DOA estimation is a major problem in array signal processing and has wide applications in radar, sonar, wireless communications, etc. With the development of sparse representation and compressed sensing, the last decade has witnessed a tremendous advance in this research topic. The purpose of this article is to provide an overview of these sparse methods for DOA estimation, with …
This work focuses on target detection in a colocated MIMO radar system. Instead of exploiting the classical temporal domain, we propose to explore the spatial dimension (i.e., number of antennas $M$) to derive asymptotic results for the detector. Specifically, we assume no a priori knowledge of the statistics of the autoregressive data generating process and propose to use a mispecified Wald-type detector, which is shown to have an asymptotic $χ$-squared distribution as $M\to\infty$. Closed-form expressions for the probabilities of false alarm and detection are derived. Numerical results are u…
In this paper, we derive an ambiguity function (AF) for the transmit beamspace (TB)-based multipleinput multiple-output (MIMO) radar for the case of far-field targets and narrow-band waveforms. The effects of transmit coherent processing gain and waveform diversity are incorporated into the AF definition. To cover all the phase information conveyed by different factors, we introduce the equivalent transmit phase centers. The newly defined AF serves as a generalized AF form for which the phased-array (PA) and traditional MIMO radar AFs are important special cases. We establish relationships amo…
Integrated Sensing and Communication (ISAC) has attracted substantial attraction in recent years for spectral efficiency improvement, enabling hardware and spectrum sharing for simultaneous sensing and signaling operations. In-band Full Duplex (FD) is being considered as a key enabling technology for ISAC applications due to its simultaneous transmission and reception capability. In this paper, we present an FD-based ISAC system operating at millimeter Wave (mmWave) frequencies, where a massive Multiple-Input Multiple-Output (MIMO) Base Station (BS) node employing hybrid Analog and Digital (A/…
İstanbul Technical University（伊斯坦布尔理工大学）；Queen’s University（女王大学）；Polytechnique Montréal（蒙特利尔理工学院）
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