Sequence design for local ambiguity function shaping in joint radar and communications

Abstract

Joint Radar and Communications (JRC) technology has gained significant attention due to its potential to enhance spectrum efficiency and reduce hardware costs. However, JRC systems suffer from Electromagnetic (EM) interference between radar and communication signals, necessitating careful sequence design. This work focuses on designing radar sequences with optimized local Ambiguity Function (AF) while ensuring spectral compatibility and hardware constraints. Specifically, we propose two optimization-based algorithms: a Semidefinite Relaxation (SDR)-based algorithm and the Augmented Lagrangian-assisted Majorization-Minimization (ALaMM) algorithm. The proposed algorithms aim to minimize the Weighted Peak Sidelobe Level (WPSL) and/or Weighted Integrated Sidelobe Level (WISL) under spectral and Peak-to-Average Ratio (PAR) constraints. Numerical simulations demonstrate that the proposed algorithms achieve significant sidelobe suppression while maintaining spectral coexistence, outperforming existing classical sequences and traditional filtering approaches.