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In this paper, we consider the unimodular sequence generation problem, and the sequences are required to possess both spectrum compatibility in the reverberant electromagnetic environment and low sidelobe levels of autocorrelation function (ACF). We proposed a template fitting approach based on the templates which define the spectrum compatibility requirements and sidelobe level requirements. First, we established the templates based on the actual sequence-feature requirements in the changing crowed-spectrum and clutter environment. Second, given an initial sequence, the spectrum shapes and the ACF features of generated sequences of proposed algorithm will approach those of templates by iterative process. Third, the iteration process come to end if the figure of merit shows convergence or meets specific requirements. The superiority of this approach is its calculation effectiveness. Specifically, it is capable of generating sequences with required power spectrum density (PSD) and ACF behaviors within much less computation load compared with some typical algorithms in open literature. Finally, some simulation results are provided to compare the spectrum compatibility and/or sidelobe suppression performance with that of SCAN (stopband cyclic algorithm new) and WeCAN (weighted cyclic algorithm new) algorithm, which prove the calculation and performance effectiveness of the proposed approach. HighlightsA template based technique for unimodular sequence design problem is proposed.The sequence is designed to consider sidelobe suppression and spectrum compatibility.The PSD and ACF templates are defined cognitively to meet the theme requirements.The TFA algorithm induces the PSD and ACF of sequences to converge to the templates.The TFA algorithm shows effectiveness in both performance and calculation aspects.

It is presumed that using multiple antennas at the transmit and receive sides can improve the radar's performance. One such improvement can be achieved in the detection of extended targets. However, in such multiple-input multiple-output systems, proper design of the transmit signals is an obstacle that can have significant influence on the performance. In this study, enforcing the peak-to-average-ratio (PAR) constraint, the authors consider the problem of transmit space-time code and receive space-time filter design of such a system detecting extended targets. In addition, the power allocation among the different antennas is another degree of freedom that should be optimised under a total power constraint. Here, the authors derive a constrained optimisation procedure for transmit code, receive filter and transmit powers, which sequentially improves the signal-to-interference plus noise ratio of the system.

The authors deal with the robust design of multiple-input–multiple-output (MIMO) space–time transmit code (STTC) and space–time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation problems. The resulting computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. At the analysis stage, they assess the performance of the proposed algorithm in terms of the achieved SINR. They show that properly exploiting the spatial degrees of freedom offered by the MIMO system, it is possible to obtain considerable SINR gains with respect to the conventional single-input–single-output system. Moreover, their results highlight the capability of the proposed method to robustify the performance of the designed system against possible knowledge inaccuracies.

We propose a novel robust design method to jointly optimize the radar transmit code and receive filter, exploiting the signal-to-interference-plus-noise ratio (SINR) at the receiver end as design figure of merit. We confer robustness to our method against uncertainties on the target impulse response (TIR) using a worst-case optimization approach. Precisely, we model the uncertainty set as a finite collection of TIRs, obtained sampling the actual TIR at some aspect angles. We further enforce a peak-to-average power ratio (PAR) constraint to the transmit code, which is very important for radar applications, where the transmitter operates close to saturation. The design problem is tackled using a sequential optimization procedure alternating between two semi-definite programming (SDP) problems, followed by randomization steps. Our numerical results highlight the robustness and applicability of the proposed method.

In this paper, we consider the problem of transmit code design to optimize the detection probability of an extended target embedded in Gaussian signal-dependent interference. We model the target with a priori known target impulse response (TIR) structure along with an unknown reflection factor. As is known, the performance of the generalized likelihood ratio test (GLRT) detector, for the case at hand, monotonically increases with the signal-to-interference-plus-noise ratio (SINR). Hence, we deal with the code design problem via maximizing the SINR. We also enforce a peak-to-average power ratio (PAR) constraint on the sought code. We devise a cyclic method to tackle the highly non-convex design problem. Numerical results highlight the effectiveness of the proposed method to improve the detection performance of the system.

Efficient combination of multiple input multiple output (MIMO) and passive coherent location (PCL) ideas is expected to improve performance of localisation schemes. While using multiple antennas at transmit and receive sides provides spatial diversity, it is possible to obtain similar performance by using multiple transmitters, already transmitting standard signals (such as digital TV) in the environment (also known as illuminators of opportunity). However, in this case, it is not always possible to ensure that signals of different transmitters are orthogonal to each other. In such cases, resolving signals of multiple transmitters reflected from multiple objects is not a trivial problem. One such scenario arises when transmitters of a single frequency network (SFN) are used. Consequently, in order to obtain the desired diversity gain, it is necessary to develop proper techniques to assign each echo arriving at the receiver to a given transmitter and a specific object to be localised. In this paper, we propose a scheme that addresses the association problem in an efficient way. Also, we consider the case of multiple antennas only at the transmit side while using a single receiver, which is the case of a multi-input single-output (MISO) system, a subset of MIMO systems, in general.