Multiple-input And Multiple-output Radar Research Articles

Joint Power and Bandwidth Allocation in Collocated MIMO Radar Based on the Quality of Service Framework

The simultaneous multi-beam working mode of the collocated multiple-input and multiple-output (MIMO) radar enables the radar to track multiple targets simultaneously. A joint power and bandwidth allocation algorithm in a collocated MIMO radar based on the quality of service (QoS) framework is proposed for the multi-target tracking problem with different threat levels. Firstly, a posterior Cramer–Rao lower bound (PCRLB) concerning the power and bandwidth is derived. In addition, the optimal objective functions of power and bandwidth are designed based on the QoS framework, and the problem is solved using the convex relaxation technique and the cyclical minimization algorithm. The numerical results show that the proposed algorithm has better tracking accuracy and achieves more reasonable resource allocation compared to strategies such as average allocation.

Modeling and Removing Doppler Division Multiplexing Spurs in Automotive MIMO Radar

Doppler division multiplexing (DDM) is a popular slow-time modulation technique for automotive multiple-input and multiple-output (MIMO) radars. It requires accurate transmit phase shifters to avoid artifacts such as spurs that would degrade the radar system’s performance. This article proposes a system impact analysis of the constellation imbalance of the phase shifter. The spurs formation is modeled in a second part to understand the information they convey on the constellation imbalance. Subsequently, this information is exploited as a base for a novel constellation imbalance estimation algorithm. The estimation is finally utilized to predistort the phase shifter. The DDM spur model and the constellation imbalance estimation method are evaluated on a recorded automotive radar dataset. The results show that the imbalance in the phase shifter constellation can be reduced such that all spurs are suppressed below the noise floor. With the presented method, the DDM MIMO radar system can autonomously evaluate when recalibration is needed and perform self-calibration on the road to maintain the system’s performance throughout its life cycle.

Towards High-Resolution Imaging With Photonics-Based Time Division Multiplexing MIMO Radar

A photonics-based time division multiplexing (TDM) multiple-input and multiple-output (MIMO) radar is proposed to realize high-resolution imaging. In this MIMO radar, multiple transmitters generate time-domain orthogonal linearly frequency modulated (LFM) signals based on microwave photonic frequency octupling and optical TDM technique, and multiple receivers implement dechirping of the multi-channel radar echoes based on microwave photonic frequency mixing. The microwave photonic techniques make the system capable to generate and process broadband radar signals, and the TDM yields a high spectral efficiency, which allows a large bandwidth in each transmitter and receiver. Meanwhile, the TDM-MIMO ensures complete orthogonality between different channels and enables good flexibility in arranging more transmit and receive channels. Therefore, the proposed photonics-based TDM-MIMO radar can achieve both high range resolution and high angular resolution. In the experiment, a photonics-based 4 × 8 TDM-MIMO radar is established which has an operation bandwidth of 8 GHz in each transmit channel. The range resolution and angular resolution are estimated to be 1.9 cm and 1.1°, respectively. A broadband back projection (BP) imaging algorithm with both frequency and time-delay dependent phase compensation is proposed, based on which high resolution imaging of single and complex targets is achieved.

4-D Gesture Sensing Using Reconfigurable Virtual Array Based on a 60-GHz FMCW MIMO Radar Sensor

A novel 4-D gesture sensing technique using reconfigurable virtual array method with a 60-GHz frequency-modulated continuous wave (FMCW) radar is presented. The 4-D sensing includes the 3-D spatial positioning and the 1-D motion tracking, which combines detection in both spatial and temporal domains. The proposed technique can be used for gesture sensing for both macro gestures such as handwriting letters and numbers, hand drawing different patterns in space and micro gestures such as the fingers’ actions of virtual slider, finger tap, and finger wave. Moreover, this work presents a method to reconfigure the working modes of different transmitting and receiving channels in the multiple input and multiple output (MIMO) architecture, which effectively increases the sensing range of the radar sensor and the signal-to-noise ratio (SNR) of the beat signal. For various gestures at different distances or in different environments, the proposed technique can adaptively achieve the best detection by reconstructing the virtual array of the MIMO radar. A series of experiments are carried out in both microwave anechoic chamber and office environments to validate the proposed technique. The experimental results show that the proposed technique performs well in sensing a variety of both macro gestures andmillimeter-level micro gestures. Compared with the conventional MIMO method, the proposed technique increases the sensing range by 3.5 times, and the SNR is also greatly improved by 12 dB when the radar performs gesture sensing at the distance of 0.65 m.

Photonics-enabled distributed MIMO radar for high-resolution 3D imaging

Three-dimensional (3D) imaging radar is an advanced sensor applied in space surveillance and target recognition for supplying 3D geometric features and supporting visualization. However, high 3D resolution requires both broadband operation and a large 2D aperture, which are difficult and complex for conventional radars. This paper presents a photonics-enabled distributed multiple-input and multiple-output (MIMO) radar with a centralized architecture. By use of photonic multi-dimensional multiplexing, multi-channel signal generation and reception are implemented on a shared reference signal in a central office, enabling a highly coherent network with a simple structure. Additionally, a sparse array and a synthetic aperture are combined to efficiently reduce the required transceivers, further weakening the dilemma between system complexity and angular resolution. A 4 × 4 MIMO radar is established and evaluated in field tests. A high-resolution 3D image of a non-cooperative aircraft is obtained, in which rich details are displayed. From a comparison with electronics-based radar, significant resolution improvement is observed. The results verify the superior imaging capability and practicability of the proposed radar and its great potential to outperform conventional technologies in target classification and recognition applications.

Joint Antenna Placement and Power Allocation for Target Detection in a Distributed MIMO Radar Network

Radar network configuration and power allocation are of great importance in military applications, where the entire surveillance area needs to be searched under resource budget constraints. To pursue the joint antenna placement and power allocation (JAPPA) optimization, this paper develops a JAPPA strategy to improve target detection performance in a widely distributed multiple-input and multiple-output (MIMO) radar network. First, the three variables of the problem are incorporated into the Neyman–Pearson (NP) detector by using the antenna placement optimization and the Lagrange power allocation method. Further, an improved iterative greedy dropping heuristic method based on a two-stage local search is proposed to solve the NP-hard issues of high-dimensional non-linear integer programming. Then, the sum of the weighted logarithmic likelihood ratio test (LRT) function is constructed as optimization criteria for the JAPPA approach. Numerical simulations and the theoretical analysis confirm the superiority of the proposed algorithm in terms of achieving effective overall detection performance.

Joint beam selection and power allocation in cognitive collocated MIMO radar for potential guidance application under oppressive jamming

The collocated multiple-input and multiple-output (MIMO) radar can track multiple targets simultanesouly under the simultaneous multi-beam (SM) working mode. In this case, each transmit beam is focused to illuminate the region of interest (ROI), and then a focused beam is formed at the receiver for higher resolution. A joint beam selection and power allocation (JBSPA) strategy for potential guidance application under oppressive jamming is developed in this mode. On account of the posterior Cramér-Rao lower bound (PCRLB) offering a quantitative measurement for target tracking accuracy, the PCRLB is derived and utilized as the optimization criterion. The optimization model is formulated with the aim of improving the effective tracking target quantity and the sum of the PCRLBs of the effective tracking targets (ETTs). By exploiting the local search based on the benefit-cost ratio (BCR), the previous JBSPA problem is converted into a convex problem, and then transformed into a semidefinite programming (SDP) problem to solve it. Numerical results demonstrate the superior performance of the proposed strategy in improving the multiple target tracking (MTT) performance.

High-Resolution Phased-Subarray MIMO Radar With Grating Lobe Cancellation Technique

A collocated phased-subarray multiple-input and multiple-output (MIMO) radar system that reduces the number of MIMO channels to implement a large antenna array is proposed. Both the transmitter (TX) and receiver (RX) arrays are divided into phased subarrays, which consist of several RF beamforming antenna elements. Each phased subarray is exploited as an MIMO channel. To estimate the angular information of targets, a hybrid beamforming technique that incorporates RF beamforming of the phased subarrays and digital beamforming of the MIMO virtual array is used. Antenna configurations of the phased-subarray MIMO radar and the corresponding virtual array are also presented. A space between the TX phased subarrays larger than one TX subarray aperture is introduced to facilitate the larger antenna aperture. Because this involves unwanted overall grating lobes, a grating lobe cancellation method is proposed using sum and difference RF subarray beams. This provides a higher angular resolution with the same number of antenna elements. The proposed phased-subarray MIMO radar concept with the corresponding grating lobe cancellation method is demonstrated by implementing a 60-GHz 16-element phased-subarray 2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\times }$ </tex-math></inline-formula> 2 MIMO frequency-modulated continuous-wave (FMCW) radar system.

A Novel Transmitter-Interpulse Phase Coding MIMO-Radar for Range Ambiguity Separation

The range ambiguity issue is a technical challenge in the radar community and has been widely discussed over the years. Researchers have given special attention to multiple-input and multiple-output (MIMO) radar to address the range ambiguity because this radar system can employ more equivalent degrees of freedom. Open studies on MIMO radar are generally based on the assumption of orthogonal waveforms, whereas radar performance is seriously limited by distributed targets due to mismatched energy. To this end, this paper deals with a novel MIMO radar transmission scheme called transmitter interpulse phase coding (TIPC) without using orthogonal waveforms. First, a set of well-designed TIPC codes are employed to modulate transmitter subarrays with the same modulated signal. Second, in the case of high pulse repetition frequency (PRF) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> , aliased echoes from different transmitted channels are directly separated by a group of simple Doppler filters; for normal PRF <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> radar systems, a technique called digital beamforming in azimuth is exploited to ensure an effective multiple waveform separation. Third, a decoding processing is performed for a further derivation of the residual TIPC matrix that is related with ambiguity order. Next, the desired and ambiguous echoes are separated by a specifically designed spatial filter that absorbs the residual TIPC matrix. Particularly, the separated signal can be used for some further applications such as increasing the observation swath. Finally, point-like target and distributed targets simulation experiments are performed to verify the feasibility of the proposed TIPC MIMO radar.

Microwave Photonic MIMO Radar for High-Resolution Imaging

A microwave photonic multiple-input and multiple-output (MIMO) radar is proposed and demonstrated to implement high-resolution imaging. In the proposed system, multiple orthogonal linearly frequency modulated (LFM) signals are generated by heterodyning between two optical frequency combs, which enables a MIMO transmitting array with a simple and reconfigurable structure. The receiving array uses photonic frequency mixing to implement multiple channel separation and de-chirp processing simultaneously. This microwave photonic MIMO radar can have a large operation bandwidth and a large equivalent aperture, which helps to achieve high-resolution imaging in both range and azimuth directions. In the experiment, a microwave photonic <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{4}\times \text{8}$</tex-math></inline-formula> MIMO radar is established with a 2-GHz bandwidth in each channel. Based on this MIMO radar, high-resolution back-projection (BP) imaging with a theoretical range resolution of 7.5 cm and azimuth resolution of 1.85° is demonstrated. The experimental results can verify the feasibility of the proposed MIMO radar, which is a good solution to high-resolution radar imaging by combining microwave photonic and MIMO technologies.

Vocal Signal Detection and Speaking-Human Localization With MIMO FMCW Radar

This article proposes a method to detect vocal signals and the corresponding locations of multiple humans using a multiple-input and multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar system. The signals of multiple humans are extracted with digital beamforming by the virtual array generated by MIMO radar processing. To remove body motion artifacts that distort the speech information detected by the radar, a body motion effect cancellation method is proposed. The technique allows recovering vocal signals from detected distorted signals by estimating phase variations due to body motions. A combination of the proposed vocal signal detection algorithm with a human localization one enables to detect speaking humans by means of the MIMO radar. Experiments verify that the proposed method can accurately locate and detect speaking humans based on their vocal vibration signals.

Parameter estimation and CRB analysis of 1‐bit colocated MIMO radar

The increasing demand for low-cost and low-power radars has led to the emergence of 1-bit sampling technology. 1-bit sampling technology is introduced in a multiple-input and multiple-output (MIMO) radar that has many advantages such as a high degree of freedom and flexible transmit beam pattern. The authors’ theoretical derivation shows that after 1-bit quantisation, the received signal can be expressed as a linear combination of infinite components, which include the original component and high-order components that can be regarded as interference terms. On this basis, the signal-to-noise-ratio (SNR) loss after 1-bit sampling at a low SNR is 1.96 dB. Furthermore, the Cramér-Rao bound (CRB) of a MIMO radar with 1-bit sampling is derived. In the derivation, the concept of 1-bit equivalent noise is proposed. At low SNRs, the equivalent noise power is π/2 (1.96 dB) times the original noise power, which is consistent with a previous derivation. Numerical simulations showed the feasibility of traditional algorithms for a MIMO radar with 1-bit sampling and the correctness of the authors’ derivation.

MIMO Radar Super-Resolution Imaging Based on Reconstruction of the Measurement Matrix of Compressed Sensing

This letter proposes a novel sparse recovery method of multiple-input and multiple-output (MIMO) radar compressed sensing (CS) imaging algorithms. This method leverages the prior structure of the measurement matrix to judge targets’ locations and to estimate the sparsity level in the grid roughly and finally inhabits the emergence of false targets in the imaging figure. Explicitly, the algorithm we propose is inspired by the orthogonal matching pursuit (OMP) algorithm. First, the measurement matrix can be divided into some submatrices by column. Then, we estimate which submatrices do not contain signal components by the algorithms we propose in this literature to achieve the reconstruction of the measurement matrix. Finally, we use the sparse Bayesian learning algorithm and the sparsity adaptive matching pursuit algorithm to recover the target location and scattering intensity. Experiments validate that the reconstruction error of the algorithm we propose is much lower than other sparse recovery algorithms, and targets in the imaging are more obvious than other algorithms.

Detection and Localization of Multiple Humans Based on Curve Length of I/Q Signal Trajectory Using MIMO FMCW Radar

A method to detect people in multiple locations using a multiple-input and multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar system is proposed. A 2-D range-angle map is estimated by digital beamforming with virtual receiver arrays obtained via the operation of time-division multiplexing (TDM) MIMO radar. Phase variations due to human vital signs and movements allow the identification of people from stationary clutter in the range-angle map. To improve the sensitivity of phase-based human detection, a curve-length (CL) method that estimates the length of the I/Q signal trajectory is proposed. The proposed method can overcome the codomain limitation of a conventional method through its use of the standard deviation of phase variations. Measurements show that the method improves the signal-to-clutter ratio (SCR) by 10 dB compared with that when using the conventional approach.

Two-Dimensional DOA Estimation of MIMO Radar Coherent Source Based on Toeplitz Matrix Set Reconstruction

In order to realize the high-precision direction of arrival (DOA) estimation of the coherent source of two-dimensional multiple-input and multiple-output (MIMO) radar, a solution is given by combining Toeplitz matrix set reconstruction. MIMO radar obtains a larger aperture with fewer arrays. Traditional two-dimensional reconstruction Toeplitz-like algorithms use part of the information in the construction of two correlation matrices or covariance matrices to construct the Toeplitz matrix when performing two-dimensional coherent source DOA estimation, which makes the information utilization incomplete and requires additional denoising processing. To solve the above problems, this paper proposes an improved Toeplitz matrix set reconstruction algorithm based on the two-dimensional reconstruction Toeplitz class algorithm. The complete array element receiving signal vector is used to construct two Toeplitz matrix sets containing complete information, and then their conjugate transposes. Multiply and sum to correct the matrix to obtain a full-rank matrix, so as to achieve the purpose of decoherence and combine the traditional ESPRIT algorithm to perform two one-dimensional reconstruction processing through rotation invariance and then perform angle matching to achieve two-dimensional coherent signal angle estimation, while avoiding additional denoising processing. Finally, the simulation results of the cross array and the L-shaped array verify the effectiveness of the algorithm in this paper and further extend it to the two-dimensional MIMO radar array model and compare it with the traditional ESPRIT-like algorithm and the REC-FBSS-ESPRIT algorithm. In comparison, the algorithm in this paper has better performance under the conditions of successful resolution, DOA estimation accuracy, and low signal-to-noise ratio.

Pattern Synthesis of MIMO Radar Based on Immune Differential Evolution Algorithm

In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed.

Power and Bandwidth Allocation for Multi-Target Tracking in Collocated MIMO Radar

A collocated multiple-input and multiple-output (MIMO) radar has the ability to track multiple targets under the simultaneous multi-beam mode, where each transmit beam is defocused to search the entire surveillance space, and then; a focused beam is formed at the receiver to achieve a higher resolution. A joint power and bandwidth allocation strategy is developed in this mode. The optimization model is established with the aim of improving the sum of weighted posterior Cramer-Rao lower bounds (PCRLBs) of multiple targets, which is predicted based on the feedback information in the tracking recursive cycle, subject to the limited power and bandwidth budget. By exploiting the convex relaxation technique and the cycle minimizer, this problem is transformed into a two-stage convex problem, and an efficient solution is provided using the cyclical optimization framework. The effectiveness of the proposed strategy is demonstrated by comparison with three uniform resource allocation methods in many cases.

코드 분할 다중화를 이용하는 MIMO-OFDM 레이다의 거리-도플러 영상형성 및 각도 추정

Frequency-division multiplexing(FDM) has the advantage of transmission signals that can be separated without interference for multiple-input and multiple-output(MIMO) radar processing. However, we propose the use of code division multiplexing because the additional phase terms from the frequency gap for signal separation affect the angle estimation performance. We assume that the monostatic MIMO radar uses an orthogonal frequency-division multiplexing waveform for a vehicle and propose assigning one chip for each sub-carrier. In our simulations, we present a range-Doppler map result and comparison with the root mean square error for angle estimation.

A Super-Resolution DOA Estimation Method for Fast-Moving Targets in MIMO Radar

Direction of arrival (DOA) estimation is an essential problem in the radar systems. In this paper, the problem of DOA estimation is addressed in the multiple-input and multiple-output (MIMO) radar system for the fast-moving targets. A virtual aperture is provided by orthogonal waveforms in the MIMO radar to improve the DOA estimation performance. Different from the existing methods, we consider the DOA estimation method with only one snapshot for the fast-moving targets and achieve the super-resolution estimation from the snapshot. Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the MIMO radar system. However, the denoise problem cannot be solved efficiently. Then, by deriving the dual norm of the new atomic norm, a semidefinite matrix is constructed from the denoise problem to formulate a semidefinite problem with the dual optimization problem. Finally, the DOA is estimated by peak-searching the spatial spectrum. Simulation results show that the proposed method achieves better performance of the DOA estimation in the MIMO radar system with only one snapshot.

Waveform Analytic Design Method for Transmit Beampattern Synthesis of Circulating Coded MIMO Radar

The transmit beampattern of multiple-input and multiple-output (MIMO) radar can be controlled by transmitting properly designed correlated waveforms. However, most of the correlated waveform design methods proposed in recent years are computational complex. For real time application, the low computational complex waveform design technique has become the interest of research. In this article, we present a waveform analytic design method for the transmit beampattern synthesis of circulating coded MIMO radar. The relationship between the parameters of linear frequency modulated (LFM) waveform and the instantaneous beam pointing angle of circulating coded MIMO radar is developed. Based on such a relationship, the analytic solutions to the parameters of LFM waveform are derived for arbitrary transmit beampattern synthesis. The computational burden of this method is negligible. Numerical simulation results demonstrate the performance of the proposed method.