This paper considers the integrated waveform design to simultaneously achieve a desired radar beampattern and multi-users communication for a dual-function Multiple-Input Multiple-Output (MIMO) system. To this end, a spatio-spectral modulation strategy via shaping the spatial waveform Energy Spectral Density (ESD) in directions of communication is proposed for the communication function, while beampattern Integrated Sidelobe Level (ISL) is minimized to enhance radar detectability. Meanwhile, Peak-to-Average Ratio (PAR) and power restrictions to comply with the current hardware technique and the mainlobe width constraint to cohere the beampattern main energy on the spatial region of interest are forced, respectively. Exploiting an equivalent reformulation of the original non-convex optimization problem, a Sequential Block Enhancement (SBE) framework that alternately updates each waveform in each emitting antenna is developed to monotonically decrease ISL. Each block involves the Dinkelbach’s procedure, sequential convex approximation and Alternating Direction Method of Multipliers (ADMM) to obtain single waveform, while the analytic proof with the converged block being a Karush-Kuhn-Tucker (KKT) point is provided. Finally, numerical results highlight the effectiveness of both the proposed dual function scheme and the waveform synthesis technique in comparison with some counterparts.

This paper deals with the problem of mainlobe jamming suppression for polarization sensitive phased-array radar system via a joint polarization-space-time processing method resorting to tensor decomposition. Firstly, a radar model accounting for one target and multiple mainlobe jammers in the far field is considered, which is equipped with a polarized transmitted antenna and a uniform linear dual-polarization receiving array. Then, exploiting the polarization-space-time characteristics, tensor CANDECOMP/PARAFAC (CP) decomposition is introduced to recast the received signal as a third order tensor consisting of three factor matrices. Further, the target echo and the jamming signal can be obtained via minimizing the Frobenius norm of the approximation error between the tensor and the outer product of the factor matrices. Finally, the effectiveness of the proposed method by numerical simulation is verified, showing its capability to combat various types of mainlobe jamming as well as their compound forms compared with the art competing method.

Integrated Sensing and Communication (ISAC) is a pivotal technology enabling next-generation 6G networks by seamlessly combining communication and sensing functionalities for emerging applications. However, practical ISAC deployments are often hindered by performance degradation in complex environments. Ground-based ISAC systems are susceptible to line-of-sight (LoS) blockages stemming from urban infrastructure and irregular terrain. While uncrewed aerial vehicle (UAV)-based ISAC has gained prominence, current research predominantly focuses on single-UAV architectures, which exhibit limitations in sensing coverage, accuracy, and vulnerability to ground clutter interference. This paper presents a collaborative multi-UAV ISAC framework designed to address these shortcomings through coordinated transmit-receive beamforming and trajectory optimization. A system-level model characterizing cooperative sensing performance of multiple UAVs in clutter-rich environments is developed. An optimization problem is formulated to maximize the signal-to-clutter-plus-noise ratio (SCNR) subject to communication quality-of-service (QoS) constraints. The resulting non-convex problem is effectively solved utilizing an alternating optimization algorithm, decomposing it into tractable beamforming design and trajectory optimization sub-problems, both of which are converted into convex forms. Numerical simulations conducted under clutter scenarios demonstrate significant improvements in sensing robustness and communication reliability achieved by the proposed framework compared to single-UAV and clutter-agnostic approaches.

This paper deals with the dual-function signal design to simultaneously achieve a desired radar beampattern and multi-user communication for a Multiple-Input Multiple-Output (MIMO) system. A novel Intra-pulse Index Modulation (I2M) methodology via jointing information embedding subpulses positions options and Differential Phase Shift Keying (DPSK) is proposed to communicate, while beampattern Integrated Sidelobe Level (ISL) is minimized to enhance radar detectability. Meanwhile, constant-envelope and communication modulation constraints are enforced to ensure compatibility with the current hardware techniques and communication demand, respectively. Besides, the mainlobe width constraint is enforced to concentrate the main energy within a specific spatial region. To tackle the resulting nonconvex and Non-deterministic Polynomial-hard (NP-hard) optimization problem, the Coordinate Descent (CD) algorithm under Multiple Phase Constraints (MPCCD) is exploited to monotonically decrease ISL, and the Consensus-Alternation Direction Method of Multipliers (C-ADMM) is utilized to attain the initial feasible sequence. Finally, numerical results highlight the effectiveness of the proposed dual-function signal design method in comparison with some counterparts.

This paper focuses on the design of a dual-function narrowband orthogonal signal set with low Cross- and Auto-correlation Peak Sidelobe Levels (C/A-PSL) to simultaneously achieve active detection and multi-user communication for the Multiple Input Multiple Output (MIMO) Dual-Function Radar and Communication (DFRC) system. A novel Intra pulse Index and Phase (Intra-IP) methodology via jointing Information embedding Subpulses (InSps) positions selection and Differential Phase Shift Keying (DPSK) is proposed to communicate. This modulation method enables the transmission of different information to distinct users in the same spatial direction. The orthogonal signal set design problem is formulated based on minimizing C/A-PSL while considering the constant envelope and phase constraints. To tackle the resulting nonconvex and NP-hard optimization problem, the Special Majorization-minimization Coordinate Descent (SM-CD) algorithm is exploited to monotonically decrease C/A-PSL. Finally, numerical results demonstrate the effectiveness of the proposed Intra-IP modulation method in comparison with some counterparts.