Presence Of Signal-dependent Interference Research Articles

Joint Transceiver Beamforming for Multi-Target Single-User Joint Radar and Communication

This letter considers the joint design of transmit and receive beamforming (TRBF) vectors for multi-target single-user joint radar and communication (JRC) systems in the presence of signal-dependent interference. An iterative framework is devised to maximize the signal-to-interference-plus-noise ratio (SINR) of a target while guaranteeing the SINRs of the user and the rest of the targets. At each iteration, the problem of designing transmit beamformer is non-convex and can be solved by semidefinite programming (SDP) optimization. Moreover, an orthogonalization-based transmit beamforming method is proposed to efficiently obtain a suboptimal analytical solution. Numerical results verify the effectiveness of the proposed framework.

Energy Efficiency Optimization in Radar-Communication Spectrum Sharing

Energy efficiency, possibly coupled with cognition-based and spectrum-sharing architectures, is a key enabling technology for green communications in 5G-and-beyond standards. In this context, the present paper considers a multiple-input multiple-output communication system cooperatively coexisting with a surveillance radar: the objective function is the communication system energy efficiency, while radar operation is safeguarded by constraining the minimum received signal-to-disturbance ratio for a set of range-azimuth cells of the controlled scene, and no time synchronization between them is assumed. The degrees of freedom are the transmit powers of both systems, the space-time communication codebook, and the linear filters at the radar receiver. The resulting optimization problem is non-convex, due to both the objective function and the presence of signal-dependent interference (clutter): we develop a block-coordinate-ascent approximate solution and offer a thorough performance assessment, so as to elicit the merits of the proposed approach, along with the interplay among the achievable energy efficiency, the density of scatterers in the environment, and the size of the set of protected radar cells.

Rao-Based Detectors for Adaptive Target Detection in the Presence of Signal-Dependent Interference

The adaptive radar detection of a point target in the presence of signal-dependent interference, also known as system-dependent clutter, is addressed in this paper. Here, the radar signal is assumed to be an intra-pulse modulated waveform and the target is surrounded by the interference, both in range and frequency spectrum domains. In a clutter-dominant situation, the detection problem is studied under wide-sense stationary (WSS) and also non-stationary Gaussian interference processes and two closed-form detectors, respectively named WSS-Rao and NS-Rao are derived. Both analytically and using computer simulations, it is shown that the proposed detectors perform independent of the transmit signal. In addition, the proposed NS-Rao and WSS-Rao detectors ensure a constant false alarm rate with respect to the statistical characteristics of the interference. Our simulations illustrate the remarkable effectiveness of the proposed detectors compared to their upper-bound. In particular, the WSS-Rao detector can be implemented by simple scalar operations. Furthermore, in WSS scenarios with a limited number of received echoes, which happens in many practical situations, the WSS-Rao detector outperforms its competitors. It was also shown through simulations that both the NS-Rao and WSS-Rao are robust with respect to the clutter distribution.

Robust Transceiver Design for Extended Target Detection in a Signal-Dependent Interference Scenario

Assuming unknown knowledge of target impulse response (TIR), this paper develops robust design methods to optimize the transceiver for the detection of extended targets in the presence of signal-dependent interference. Two different transceiver design schemes comprising single filter and multiple filters methods are presented to handle the fact that the TIR of extended target is unknown at the transmit side. The lowest signal to interference plus noise ratio (SINR) is considered at the receiver side as the performance measure of the system. Two robust design problems are formulated as max-min optimization problems to robustify the system SINR with respect to the unknown TIR. The former is solved using an iterative optimization process alternating between two sequential semi-definite programming (SDP) problems; the latter is solved employing an iterative optimization procedure alternating between a convex and a generalized fractional programming problems. Finally, several numerical examples highlight that the proposed design schemes have better robustness compared to several counterparts which are presented in open literature.

Riemannian Geometric Optimization Methods for Joint Design of Transmit Sequence and Receive Filter on MIMO Radar

In this paper, we study the joint design of a transmit sequence and a receive filter for an airborne multiple-input multiple-output (MIMO) radar system to improve its moving target detection performance in the presence of signal-dependent interference. The optimization problem is formulated to maximize the output signal-to-noise-plus-interference ratio (SINR), subject to the waveform constant-envelope (CE) constraint. To address the challenge of this non-convex problem, we propose a novel optimization framework for solving the problem over a Riemannian manifold which is the product of complex circles and a Euclidean space. Manifold optimization views the constrained optimization problem as an unconstrained one over a restricted search space. The Riemannian gradient descent algorithms and the Riemannian trust-region algorithm are then developed to solve the reformulated problem efficiently with low iteration complexity. In addition, the proposed manifold-based algorithms provably converge to an approximate local optimum from an arbitrary initialization point. Numerical experiments demonstrate the algorithmic advantages and performance gains of the proposed algorithms.

Joint Design of the Transmit and Receive Beamforming in MIMO Radar Systems

In this paper, we investigate the problem of joint design of the transmit and receive beamforming weight vectors for multiple-input multiple-output (MIMO) radar systems in the presence of signal-dependent interference, which is distinct from its existing counterparts focusing on joint design of the temporal codes of transmit waveforms and spatial-temporal receive filter. The design problem is formulated as output signal-to-interference-plus-noise ratio (SINR) maximization subject to a similarity constraint on the transmit beamforming weight, such that a good transmit beampattern can be guaranteed. Due to the existence of signal dependence, the resultant problem is NP-hard, and therefore, an iterative scheme is devised. Specifically, in each iteration, the receive beamforming is optimized with the minimum variance distortionless response method, then the transmit beamforming is obtained via the semidefinite relaxation (SDR) technique. It is proved that the proposed SDR-based algorithm is able to produce a rank-one solution. Numerical simulations are provided to demonstrate the effectiveness of the proposed algorithm.

Interference cancellation in co‐located MIMO radars using waveform optimisation in signal dependent clutter

In this study, two iterative design algorithms for multiple-input multiple-output (MIMO) radars with co-located antennas with point targets are proposed. In these algorithms, by joint design of the receiver filter and transmit waveform using linear combination of orthogonal waveforms, the authors aim to maximise the signal-to-interference plus-noise ratio (SINR) in the presence of signal dependent interference. In the first proposed algorithm, in each iteration, transmit waveforms and receive filter are designed in closed form to decrease the computational complexity. In the second method, by adding constant envelope criteria, the final waveform would be a linear combination of orthogonal waveforms and because of using a constant envelope, combining coefficients have equal magnitudes and different phases. Therefore, it is more practical for hardware implementation in comparison to the first proposed method. Simulation results show that both proposed methods have better SINR performances compared with other methods proposed in MIMO radar literature. The outperformance of the second proposed method with respect to phased arrays shows that by only using phase shifted combination of orthogonal waveforms, better performance in comparison to phased array radars can be achieved.

Joint Optimization of Transmit Waveform and Receive Filter for Target Detection in MIMO Radar

In this paper, we consider the joint optimization of transmit waveform and receive filter in colocated multiple-input multiple-output (MIMO) radar to enhance target detection performance in the presence of signal-dependent interference. It is noticed that in the detection stage, the output energy is mainly concentrated in the mainlobe region. Therefore, we decompose the receive filter as the cascade of a receive beamformer and a temporal filter. Then, under the peak-to-average ratio (PAR) constraint, a problem is formulated to realize a trade-off between the signal-to-interference-plus-noise ratio (SINR) and the integrated sidelobe level (ISL) at the pulse compression output of mainlobe synthesized signal. A non-decreasing algorithm, which is the combination of sequential optimization algorithm and minorization-maximization (MM) method, is developed to solve this problem. Besides, in order to reduce computation burden, a special case is proposed, where we fix the temporal filter as the mainlobe synthesized signal. Then, another non-decreasing algorithm based on the MM method is proposed to solve the special case. Numerical experiments show that the proposed algorithms can obtain high output SINR and low output ISL efficiently.

Colocated MIMO Radar SINR Maximization Under ISL and PSL Constraints

This letter considers joint design of transmit waveform and receive filter in colocated multiple-input multiple-output (MIMO) radars in order to enhance target detection performance in the presence of signal-dependent interference. Here, signal-to-interference-plus-noise ratio (SINR) is maximized under the practical constraints of integrated sidelobe level (ISL) and peak sidelobe level (PSL) at the pulse compression output. We have also shown that the joint transmit signal and receive filter design can be formulated as a convex optimization problem, which can be efficiently solved using optimization toolbox (CVX). Simulation results show that our proposed algorithm is able to suppress interference efficiently under ISL and PSL constraints and get close to the SINR efficiency of unconstrained methods.

MIMO Radar Waveform Design With PAPR and Similarity Constraints

The paper investigates the joint design of transmit waveform and receive filter for multiple-input multiple-output radar in the presence of signal-dependent interference, subject to a peak-to-average-power ratio constraint as well as a waveform similarity constraint. Owing to this kind of signal dependence and constraints, the formulated optimization problem of the output signal-to-interference-plus-noise ratio (SINR) maximization is NP-hard. To this end, an auxiliary variable is first introduced to modify the original problem, and then a primal-dual algorithm based on the block successive upper-bound minimization method of multipliers (BSUM-M) is developed to deal with the resulting problem. Moreover, an active set method is exploited to solve the quadratic programming problem involved in each update procedure of the proposed BSUM-M algorithm. Finally, numerical simulations are performed to demonstrate the superiority of the proposed algorithm over state-of-the-art methods in terms of the output SINR, beampattern, computational complexity, pulse compression, and ambiguity properties.

Design of measurement matrix in CS-MIMO radar for extended target estimation

In this paper, we propose a measurement matrix design that improves the parameter estimation of an extended target in a compressive sensing multiple-input multiple-output (CS-MIMO) radar system. In our signal model, we consider the target impulse response (TIR) as an unknown vector that should be estimated in a compressive sensing scenario. Our proposed measurement matrix optimization method is based on minimizing the trace of the Cramer–Rao lower bound (CRLB) matrix in the presence of signal-dependent interference and receiver noise, which leads to a nonlinear and non-convex optimization problem. To tackle design problem, we propose a three-stage optimization procedure in which a low rank matrix constraint is enforced. For comparison purpose, we also obtain the measurement matrix based on minimizing the block-coherence of the sensing matrix blocks. Numerical results demonstrate the effectiveness of our proposed method in parameter estimation of extended targets for CS-MIMO radar.

An Information Theoretic Approach to Robust Constrained Code Design for MIMO Radars

The problem of transmit code design in multiple-input multiple-output (MIMO) radar systems is addressed in this paper. The problem is considered in both colocated and widely separated antenna radars in the presence of signal-dependent interference and target mobility. Due to complexity of exact expressions of the optimal detector in the MIMO radars, information theoretic criteria are employed as design metrics which results in a general form of nonconvex optimization problems. In order to tackle the problem, a novel technique based on the minorization-maximization algorithm is proposed and solutions are presented under practical constraints on the transmit code, namely energy constraint, peak-to-average-power ratio constraint, and similarity constraint. Furthermore, the devised method is extended to be robust against uncertainties of the clutter and interference statistics. Finally, numerical examples are used to show the performance of the proposed technique in different situations.

A New Iterative Approach in SINR Improvement of MIMO Radars by Using Combination of Orthogonal Waveforms

In this paper we consider joint waveform and filter design in multi-input multi-output (MIMO) radars in the presence of signal dependent interference to improve signal-to-interference-plus-noise ratio (SINR) of received signals. We have proposed two new iterative methods for this in which instead of direct design of waveforms, the coefficients of orthogonal waveform combinations are designed. In the first method, coefficients of combinations are calculated by solving a convex optimization problem. By extending the first method, we have proposed a method for multi-target case in presence of signal dependent interference. However, the computational complexity of the first method is high and therefore we have proposed the second method, which is more suitable for real time applications. In the second method, in each step, waveform combination coefficients and received filter coefficients are designed in closed form. Simulation results show that the proposed methods can achieve higher SINR in comparison to other methods which are used in MIMO and phased array radars.

Optimizing Radar Waveform and Doppler Filter Bank via Generalized Fractional Programming

Assuming unknown target Doppler shift, we focus on robust joint design of the transmit radar waveform and receive Doppler filter bank in the presence of signal-dependent interference. We consider the worst case signal-to-interference-plus-noise-ratio (SINR) at the output of the filter bank as the figure of merit to optimize under both a similarity and an energy constraint on the transmit signal. Based on a suitable reformulation of the original non-convex max-min optimization problem, we develop an optimization procedure which monotonically improves the worst-case SINR and converges to a stationary point. Each iteration of the algorithm, involves both a convex and a generalized fractional programming problem which can be globally solved via the generalized Dinkelbach’s procedure with a polynomial computational complexity. Finally, at the analysis stage, we assess the performance of the new technique versus some counterparts which are available in open literature.

Characterizations of PAPR-Constrained Radar Waveforms for Optimal Target Detection

We propose to design a peak-to-average power ratio (PAPR) constrained transmit waveform that achieves the optimal performance (following the Neyman-Pearson lemma) in detecting a target in the presence of signal-dependent interference. The direct time-domain approach allows straightforward characterizations of the correlation and PAPR properties of the designed signals, which are critically important to analyze the system performance in the presence of multiple targets and to assess the transmitter power-utilization, respectively. Therefore, instead of designing a transmit signal only for the optimal detection performance, we solve a biobjective Pareto-optimization problem, subjecting to the PAPR and total energy constraints, in order to simultaneously optimize the detection and cross-correlation performances. With extensive numerical examples, we demonstrate that PAPR-constrained signals produce nearly optimum detection performance even with a strict PAPR requirement, and also highlight the conflicting behavior of the detection and correlation performances.

A Doppler Robust Design of Transmit Sequence and Receive Filter in the Presence of Signal-Dependent Interference

In this paper, we study the joint design of Doppler robust transmit sequence and receive filter to improve the performance of an active sensing system dealing with signal-dependent interference. The signal-to-noise-plus-interference (SINR) of the filter output is considered as the performance measure of the system. The design problem is cast as a max-min optimization problem to robustify the system SINR with respect to the unknown Doppler shifts of the targets. To tackle the design problem, which belongs to a class of NP-hard problems, we devise a novel method (which we call DESIDE) to obtain optimized pairs of transmit sequence and receive filter sharing the desired robustness property. The proposed method is based on a cyclic maximization of SINR expressions with relaxed rank-one constraints, and is followed by a novel synthesis stage. We devise synthesis algorithms to obtain high quality pairs of transmit sequence and receive filter that well approximate the behavior of the optimal SINR (of the relaxed problem) with respect to target Doppler shift. Several numerical examples are provided to analyze the performance obtained by DESIDE.

Robust Transmitted Waveform and Received Filter Design for Cognitive Radar in the Presence of Signal-Dependent Interference

The problem of robust transmitted waveform and received filter design for cognitive radar in a signal-dependent interference environment is considered. When estimate errors of the target impulse response (TIR) and clutter impulse response (CIR) exist, in order to improve the worst signal-to-clutter ratio (SCR) and signal-to-interference-and-noise ratio (SINR), a robust transmitted waveform and received filter are designed based on the minimax criterion by using the information fed back from the receiver. Using deterministic and random models, the waveform and filter design problem is divided into three optimization problems. The robust waveform and filter are then obtained by solving these problems. In the deterministic model, we prove that the robust waveform and filter impulse response can be generated by a pseudorandom code. In the random model, the robust waveform and filter impulse response can be obtained by an alternative projection algorithm. Numerical results indicate that the worst SINR of the robust waveform and filter is higher than that of the traditional waveform and filter.

Signal detection for cognitive radar

The problem of signal detection for cognitive radar (CR) is considered, and a closed-loop detection system is proposed to detect the extended target in the presence of signal-dependent interference. In the system, the estimator of target impulse response (TIR) and waveform design are used to improve the detection performance of CR, and the estimate of TIR is also used for designing the matched waveform. In addition, in order to improve the reliability of detection, the two-step process which is called estimation before detection is proposed. Simulation results indicate that the proposed system performs better than the traditional radar system which used the fixed waveform.

Waveform design in signal-dependent interference and application to target recognition with multiple transmissions

The authors present illumination waveforms matched to stochastic targets in the presence of signal-dependent interference. The waveforms are formed by SNR and mutual information (MI) optimisation. We also use these waveforms in cognitive radar (CR) target identification application. In this application, the radar system attempts to identify a deterministic or random target using multiple transmissions. These transmissions are adaptively modified in response to previously received echoes. In addition, the authors present a new multi-band application of the CR platform.

Optimal transmit-receiver design in the presence of signal-dependent interference and channel noise

Optimal detection of a target return contaminated by signal-dependent interference, as well as additive channel noise, requires the design of a transmit pulse f(t) and a receiver impulse response h(t) jointly maximizing the output signal to interference plus noise ratio (SINR). Despite the highly nonlinear nature of this problem, it has been possible to show that f(t) may always be chosen minimum-phase. A full analysis concludes with the construction of an effective numerical procedure for the determination of optimal pairs (f,h) that appears to converge satisfactorily for most values of input SINR. Extensive simulation reveals that the shape of f(t) can be a critical factor. In particular, the performance of a chirp-like pulse is often unacceptable, especially when clutter and channel noise are low-pass dominant and comparable.