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Phase-modulated continuous-wave (PMCW) radar is an emerging technology in various civilian applications. Due to the high bandwidth of the PMCW signal, it needs high-speed analog-to-digital converters (ADCs). High-resolution ADCs supporting this high bandwidth are expensive, have a big size on the chip, and consume high power, which are significant challenges for radar. A solution to deal with the aforementioned challenges is to use low-resolution, or in the most extreme case, one-bit ADCs. In this article, we aim at designing the transmit code and the receive filter for the PMCW radar in the presence of one-bit ADC at the receiver side. To this end, we introduce the mean integrated sidelobe level metric, called MISL. MISL generalizes the well-known ISL metric for nonideal ADC usage at the receiver side and takes the effect of noise and target backscattering coefficient into account. For mathematical tractability, we employ the maximum likelihood estimation of the target backscattering coefficient. This leads to casting an optimization problem that does not need knowledge about noise and target characteristics. We utilize the cyclic optimization procedure to optimize the transmit code and the receive filter. The filter design subproblem admits a closed-form solution, whereas we obtain a solution to transmit code design subproblem via the coordinate descent framework. Numerical examples illustrate the superior performance of the proposed method compared to benchmarks that design sequences assuming ideal ADC at the receiver. [ABSTRACT FROM AUTHOR]

Compared to the uniform linear array (ULA), the sparse linear array (SLA) has many advantages such as a greater degrees of freedom (DOF), a higher resolution, and robustness against mutual coupling. The optimal placement of elements to achieve the maximum DOF in SLA has been an old problem in array signal processing. Finding the optimum placement is limited to an exhaustive computer search as yet. Therefore, some familiar SLAs (such as ‘nested’ and ‘coprime’ arrays) have been suggested to improve DOF although none of them necessarily can achieve the maximum DOF with a certain number of sensors. In this paper, first we have proposed a novel hole-free SLA that yields the minimum number of sensors (MSA) for the desired DOF. The optimization problem associated with such an array is a nonlinear binary optimization problem. Then, the problem is transformed into a binary linear programming (BLP) problem which could be solved exactly. Using the proposed method, a fast and efficient solution to the minimum redundancy array(MRA) is found. Finally, the simulation results show that the proposed array has a higher DOF compared to the other competitive methods for a given number of sensors, which is the maximum possible DOF. This can lead to a better target resolution and DOA estimation. [ABSTRACT FROM AUTHOR]

This paper is focused on the design of phase sequences with good (aperiodic) autocorrelation properties in terms of peak sidelobe level and integrated sidelobe level. The problem is formulated as a biobjective Pareto optimization forcing either a continuous or a discrete phase constraint at the design stage. An iterative procedure based on the coordinate descent method is introduced to deal with the resulting optimization problems that are nonconvex and NP-hard in general. Each iteration of the devised method requires the solution of a nonconvex min–max problem. It is handled either through a novel bisection or an FFT-based method respectively for the continuous and the discrete phase constraint. Additionally, a heuristic approach to initialize the procedures employing the $l_p$-norm minimization technique is proposed. Simulation results illustrate that the proposed methodologies can outperform some counterparts providing sequences with good autocorrelation features especially in the discrete phase/binary case. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the power allocation issue for cooperative-sensing-based code-division multiple access (CDMA) cognitive radio (CR) networks. We consider a network consisting of multiple secondary users (SUs) and a secondary base station (BS) implementing a two-phase protocol. In the first phase, censor-based cooperative spectrum sensing is carried out to detect the PU's presence. When the channel is estimated to be free, SUs transmit data in the uplink to the BS in the second phase by using CDMA. We optimize the sensing parameters and transmit power of SUs jointly to minimize the total energy consumption with the constraints on SUs' quality of service (QoS) and detection probability of the PU. This is a nonconvex problem, which we represent as a monotonic optimization problem and solve by means of monotonic programming. Furthermore, we study the separate optimization problem in which sensing parameters and transmit power are optimized to minimize the energy consumption of the first phase and the second phase disjointly. Numerical results show that the proposed joint optimization method saves energy consumption significantly in lower signal-to-noise ratios (SNRs). It can introduce as high as 3.9 and 8.7 dB joule energy saving per time slot in zero-sensing SNR under the same data rate constraints of 0.5 and 1 bit/s/Hz, respectively. [ABSTRACT FROM PUBLISHER]

Multiple pulse repetition frequency (PRF) radars are used for increasing the maximum unambiguous range and Doppler frequency. Because of the nonuniform transmitted pulses, special techniques are required for spectrum analysis of the received signal in these radars. An algorithm for spectrum analysis of multiple PRF radars is presented here. The algorithm is based on the compressive sensing (CS) theory and uses the sparse characteristic of received signal in frequency domain and universal sampling pattern of multiple PRF pulses for determining the Doppler frequencies of targets. Moreover, a CS-based algorithm for blind estimation of the number of targets is presented. The proposed algorithms work properly in low sampling rates and in the presence of multiple targets and Gaussian clutter. Simulation results are presented for illustrating high performance of the algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of code design to improve the detection performance of multi-static radar in the presence of clutter (i.e., a signal-dependent interference). To this end, we briefly present a discrete-time formulation of the problem as well as the optimal detector in the presence of Gaussian clutter. Due to the lack of analytical expression for receiver operation characteristic (ROC), code design based on ROC is not feasible. Therefore, we consider several popular information-theoretic criteria including Bhattacharyya distance, Kullback-Leibler (KL) divergence, J-divergence, and mutual information (MI) as design metrics. The code optimization problems associated with different information-theoretic criteria are obtained and cast under a unified framework. We propose two general methods based on Majorization-Minimization to tackle the optimization problems in the framework. The first method provides optimal solutions via successive majorizations whereas the second one consists of a majorization step, a relaxation, and a synthesis stage. Moreover, derivations of the proposed methods are extended to tackle the code design problems with a peak-to-average ratio power (PAR) constraint. Using numerical investigations, a general analysis of the coded system performance, computational efficiency of the proposed methods, and the behavior of the information-theoretic criteria is provided. [ABSTRACT FROM AUTHOR]