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In netted colocated multiple-input multiple-output (MIMO) radar system (NCMRS), constrained to the limited resource, one must decide when to run the NCMRS, which nodes are to be activated, how much energy should be consumed, and which waveform type as well as parameter should be transmitted by each activated node. To this end, in this article, we consider the problem of joint waveform control and space-time resource management for maneuvering targets tracking in NCMRS. First, the joint waveform type as well as parameter selection and space-time resource management optimization model is proposed, where both the network system resource consumption and the overall tracking performance of maneuvering targets are considered and employed as the network comprehensive cost. Then, to solve the established optimization problem efficiently, a modified particle swarm optimization (MPSO)-based joint waveform control and space-time resource optimization (JWCSTRO) algorithm is put forward. In the MPSO-based JWCSTRO algorithm, the system sampling period, the activated nodes, the node-target assignment, and the subarray number, transmit energy and transmit waveform type, as well as parameter of each activated node can be adjusted jointly and adaptively, where the former five implement the space-time resource optimization and the last one achieves the waveform control in NCMRS. Finally, numerical simulation results demonstrate the effectiveness of the proposed MPSO-based JWCSTRO algorithm. Furthermore, compared with the five other benchmark algorithms, the maximum and minimum improvement ratios of the network comprehensive cost of the proposed MPSO-based JWCSTRO algorithm are 44.89% and 21.68%, respectively. [ABSTRACT FROM AUTHOR]

This letter proposes a limited-memory receive filter design to maximize the output signal-to-interference-plus-noise ratio (SINR) of massive multiple-input multiple-output (MIMO) radar. The associated problem is a minimum variance distortionless response (MVDR) one which can be analytical solved, but the computation of the MVDR solution would be prohibitive in the context of massive MIMO radar, due to the huge memory consumption. To this end, we propose a low-complexity algorithm that exploits a reparameterization method to avoid the significant memory consumption, and solves the resulting problem with several simple algebraic operations. We show that the memory consumption of the proposed algorithm depends on the number of interference sources. Therefore, for the scenario with a large number of interference sources, we extend the proposed algorithm by the alternating direction method of multipliers (ADMM), which promotes a further memory reduction. Finally, numerical simulations are conducted to demonstrate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Extremely low-resolution (e.g. one-bit) analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) can substantially reduce hardware cost and power consumption for MIMO radar especially with large scale antennas. In this paper, we focus on the detection performance analysis and joint design for the MIMO radar with one-bit ADCs and DACs. Specifically, under the assumption of low signal-to-noise ratio (SNR) and interference-to-noise ratio (INR), we derive the expressions of probability of detection ($\mathcal {P}_{d}$) and probability of false alarm ($\mathcal {P}_{f}$) for one-bit MIMO radar and also the theoretical performance gap to infinite-bit MIMO radars for the noise-only case. We further find that for a fixed $\mathcal {P}_{f}$ , $\mathcal {P}_{d}$ depends on the defined quantized signal-to-interference-plus-noise ratio (QSINR), which is a function of the transmit waveform and receive filter. Thus, an optimization problem arises naturally to maximize the QSINR by joint designing the waveform and filter. For the formulated problem, we propose an alternating waveform and filter design for QSINR maximization (GREET). At each iteration of GREET, the optimal receive filter is updated via the minimum variance distortionless response (MVDR) method, and due to the difficulty in global optimality, an alternating direction method of multipliers (ADMM) based algorithm is devised to efficiently find a high-quality suboptimal one-bit waveform. Numerical simulations are consistent to the theoretical performance analysis and demonstrate the effectiveness of the proposed design algorithm. [ABSTRACT FROM AUTHOR]

This communication proposes a convex optimization algorithm to synthesize desirable beampattern for phased array with the dual-phase-shifter (DPS) structure. In the DPS structure, dual phase shifters are combined into one beamforming weight. Compared with conventional phased array, the moduli of the weight vector are not necessarily fixed constants in the DPS structure but can be changed in a continuous interval. For this reason, we propose a method that turns the beampattern synthesis problem into a convex optimization problem. The method can be readily implemented and efficiently solved using freely accessible routines. We consider how to obtain the weight vector with two beampattern synthesis problems. The first one is to maximize the mainlobe gain (or minimize the mainlobe loss) when the notch level is determined. The second one is to minimize the notch level when the mainlobe gain (or the mainlobe loss) is determined. In both cases, we can get suboptimal solutions. Under different situations, numerical results of simulations confirm the effectiveness of the two algorithms. [ABSTRACT FROM AUTHOR]

This article considers the problem of target detection for applications with limited training samples. Dimensionality reduction in the angle-Doppler domain is considered. An algorithm for selecting the best angle-Doppler channels that maximize the output signal-to-clutter-plus-noise ratio in space-time adaptive processing (STAP) is proposed. Compared with several existing STAP methods, the proposed method can achieve better clutter suppression performance at lower computational complexities when the degrees of freedom of the STAP system are fixed. Moreover, the proposed method can help address the issue of training data shortage, which may be particularly attractive for heterogeneous scenarios. Simulations are conducted for validating the proposed method and demonstrating their high performance. [ABSTRACT FROM AUTHOR]

The sky-wave over-the-horizon radar is easily interfered with by radio frequency interference (RFI) since the high-frequency band is shared by many radio devices. Various RFI suppression techniques have been developed by both spatial and temporal processing. However, in practice, where the interference characteristic is usually unknown, it is still hard to evaluate the effects of interference suppression. In this letter, the Tamura coarseness is introduced as an indicator to evaluate the RFI and its suppression algorithms. By analyzing the range-Doppler maps with RFI, the relationship between coarseness and signal-to-interference-plus-noise ratio is established. An application example of coarseness is also given, in which the diagonal loading factor of adaptive beamformer is optimized. The analysis of coarseness and performance of proposed scheme are demonstrated by experimental data. [ABSTRACT FROM AUTHOR]

This paper considers the problem of co-existence of collocated multiple-input multiple-output (MIMO) radar and downlink multiple-input single-output (MISO) communication systems, which share the same frequency band. As the interference caused by the communication systems would degrade the accuracy of radar target localization, we formulate the co-design of radar waveform and communication transmit weights by minimizing the Cramér-Rao Bound (CRB) of direction-of-arrival (DOA) estimation, subject to a set of constraints accounting for the worst-case signal-to-noise-plus-interference ratio (SINR), similarity and energy. However, the objective is nonconvex and all variables are coupled together in the SINR constraints, the formulated problem is thus NP-hard. Towards that end, a decentralized block successive upper-bound minimization (D-BSUM) method based on the decomposition theory is developed. More specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and communication weights are obtained by exploiting the semidefinite programs (SDP). It is also proved that the proposed SDP-based method gives a rank-one solution. Numerical simulations are conducted to evaluate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a flexible array response control algorithm via oblique projection, abbreviated as FARCOP, and its application to array pattern synthesis. The proposed FARCOP algorithm stems from the adaptive array theory, and it can flexibly, precisely and simultaneously adjust the array response levels at multiple angles based on an arbitrarily given weight vector. Different from the existing approaches, the proposed FARCOP algorithm controls multi-point responses by linearly transferring the given weight vector, with a transformation matrix containing a set of parameters, each of which can be very easily determined by the desired response level (at the control angle). Owing to the fact that those parameters are independent of each other, the response levels at the control angles can be either individually or jointly and, therefore, flexibly adjusted. Since the parameter phases can be arbitrary, we take the beampattern into account and propose to uniquely choose the optimal parameters under the typical criterion of maximum white noise gain (WNG). Accordingly, a gradient projection (GP) algorithm is devised to achieve the optimal solution. Moreover, a closed-form solution is derived for the centro-symmetric array. In addition, the application of the FARCOP algorithm to pattern synthesis is discussed. Comparing to the state-of-the-art methods like multi-point accurate array response control (${\text {MA}}^2{\text {RC}}$), the proposed FARCOP algorithm controls the array responses more flexibly with lower computational complexity. Representative examples are presented to demonstrate the effectiveness and superiority of the FARCOP algorithm under various situations. [ABSTRACT FROM AUTHOR]

This paper presents a new method to synthesize high-performance beampatterns, with the aid of linear fractional semidefinite relaxation (LFSDR) technique and a quasi-convex optimization approach. We consider two beampattern synthesis problems. The first one is how to determine the weight vector to maximize the array gain (or equivalently, to minimize the gain loss in mainlobe), under the condition that the amplitude response satisfies specific requirements. The second one is how to minimize the notch level at a given region, on the premise of a permissible gain loss in mainlobe. To these ends, two nonconvex optimization problems are first formulated and then relaxed to their quasi-convex forms, by using the LFSDR technique. To further solve the resultant problems, the bisection method, which is commonly used in quasi-convex optimization, is adopted. Suboptimal solutions to the original nonconvex problems are finally obtained through eigenvalue decomposition or randomization manipulations. The proposed method performs well in both the cases described earlier. Moreover, our method is not limited to the array configurations and/or noise environments. Representative simulations are presented to demonstrate the effectiveness of the proposed method in high-performance beampattern synthesis. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of the spectrally compatible waveform design for multiple-input multiple-output (MIMO) radar in the presence of multiple targets and signal-dependent interference. Unlike the existing approaches to designing the waveform for a single target via output signal-to-interference-plus-noise ratio (SINR) maximization, a new method is proposed to deal with a more general problem, i.e., designing a spectrally compatible waveform for multiple targets, by minimizing the waveform energy of the overlayed space-frequency bands under constraints of waveform similarity and individual SINR requirements. Due to the existence of signal dependence, the formulated optimization problem is NP-hard. Toward this end, an iterative algorithm is developed. Concretely, at each iteration, the receive filter is first obtained with the aid of the minimum variance distortionless response method, then the transmit waveform is optimized by employing the dual ascent method. Both the convergence and asymptotic optimality of this algorithm are discussed. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper considers the joint design of a multiple-input multiple-output (MIMO) radar with co-located antennas and a MIMO communication system. The degrees of freedom under the designer's control are the waveforms transmitted by the radar transmit array, the filter at the radar array and the code-book employed by the communication system to form its space-time code matrix. Two formulations of the spectrum sharing problem are proposed. First, the design problem is stated as the constrained maximization of the signal-to-interference-plus-noise ratio at the radar receiver, where interference is due to both clutter and the coexistence structure, and the constraints concern both the similarity with a standard radar waveform and the rate achievable by the communication system, on top of those on the transmit energy. The resulting problem is nonconvex, but a reduced-complexity iterative algorithm, based on iterative alternating maximization of three suitably designed subproblems, is proposed and analyzed. In addition, the constrained maximization of the communication rate is also investigated. The convergence of all the devised algorithms is guaranteed. Finally, a thorough performance assessment is presented, aimed at showing the merits of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust quasi-adaptive beamforming (RQAB) scheme against direction-of-arrival (DOA) mismatch. Unlike existing robust adaptive beamforming (RAB) methods, the proposed approach obtains the ultimate beamformer weight vector in a quiescent manner, nevertheless, it possesses the remarkable ability of interference rejection and desired signal reception. In this method, a two-step procedure is devised to design the quasi-adaptive weight vector. More specifically, the conventional sample matrix inversion (SMI) beamformer is first applied to find out all notch angles outside the region of interest (ROI) where the desired signal comes with a high probability. It is shown that these notch angles contain the DOAs of interferences. Then, a multipoint accurate array response control ( $ {\text {MA}}^2\text {RC}$ ) algorithm is utilized to synthesize a beampattern with the same sidelobe notch levels as the SMI, and nearly constant response over the ROI. Contrary to conventional approaches that are vulnerable to the contamination of the training data by the desired signal, our proposed approach exhibits outstanding performance under this common scenario. Moreover, besides the DOA mismatch, the proposed approach is also insensitive to the SNR, number of snapshots and mismatch angle. Additionally, different from many optimization-based RAB methods, the proposed RQAB approach offers an analytical expression of the beamformer weight vector and, hence, is computationally attractive. Typical simulation examples are provided to demonstrate the superiority of the RQAB scheme. [ABSTRACT FROM AUTHOR]

This paper presents a novel accurate array response control algorithm, abbreviated as \text A^2\text RC, and its application to array pattern synthesis. The proposed \text A^2\text RC algorithm deals with the problem of how to accurately control the array response at a given direction. Starting from the adaptive array theory, a deep analysis of the optimal weight vector is carried out. It is found that the normalized response at a given direction can be accurately adjusted to an arbitrary level, by means of making some simple modification to the initial weight vector. On this basis, all possible weight vectors, which have a specific form and can make the normalized response at the given direction equal to the prescribed value, are first figured out. Then, an effective approach to selecting the most appropriate one, which would cause the least pattern distortion, is devised. By applying the \text A^2\text RC algorithm, a new pattern synthesis approach for arbitrary arrays is developed. In this approach, the array pattern is adjusted in a point-by-point manner by successively modifying the weight vector. Contrary to the conventional approaches that assign artificial interferences in an ad hoc way, our approach is able to obtain the weight vector without iteratively determining the powers of the artificial interferences. Extensive simulation results are provided to demonstrate the performance of the \text A^2\text RC algorithm in array response control and the effectiveness of this algorithm in pattern synthesis under various situations. [ABSTRACT FROM PUBLISHER]