arXiv subjects

Ahmad Musallam

Publications and source records attributed to Ahmad Musallam.

3 recordsLinked to original sources

arXiv2026

Target Localization and Self-Calibration in a Multistatic Radar System

Target localization in a multistatic radar system, where multiple receivers cooperate to improve target positioning accuracy, has many applications, including cooperative simultaneous localization and mapping (SLAM) and autonomous robot networks. A key challenge in these applications is the uncertainty in the position and orientation (pose) of the radar receivers due to platform mobility. This work investigates the achievable improvements in both target localization and receiver pose estimation by deriving the Cramer-Rao lower bound (CRLB) for a multistatic radar system performing bistatic range and bearing measurements. We propose an alternating weighted least-squares algorithm that jointly optimizes target and receiver parameters. Monte Carlo simulations demonstrate that the algorithm performance approaches the CRLB for low to moderate noise levels.

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arXiv2026

Enhancing Sensing Privacy in ISAC Through Joint Signal and Artificial Noise Beamforming

Integrated sensing and communications (ISAC) is a promising feature in 6G networks. It is envisioned to enhance spectral efficiency and provide sensing and communication services that meet the stringent requirements of future applications. However, it also poses new security and privacy concerns by giving malicious attackers access to new information about the network. In this work, we focus on the sensing privacy of a monostatic ISAC system by investigating the capability of a sensing eavesdropper (EVE) with an unknown location, acting as a passive bistatic radar (PBR) to gain access to user location information. We then propose a joint transmit and artificial noise (AN) beamforming optimization problem to degrade EVE's performance. Finally, we propose an iterative algorithm to solve the proposed optimization problem and evaluate its performance.

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arXiv2026

Blind OFDM-ISAC Relying on Asymmetric Modem Constellations

Integrated sensing and communication (ISAC) is increasingly expected to operate under aggressive spectrum reuse, where co-channel orthogonal frequency division multiplexing (OFDM) interference can be catastrophic for data recovery on the time-frequency (TF) grid. We show that supporting blind ISAC is feasible by exploiting a fundamental asymmetry in the impact of co-channel OFDM interference: while communication is fragile on the TF grid, sensing depends on structured physical parameters whose signatures remain identifiable by relying on higher-order statistics. Based on this observation, we construct a fourth-order measurement tensor from the received OFDM signal whose coherent component preserves the delay-, Doppler-, and angle-dependent phase evolution of each source. We then develop a three-dimensional higher-order-statistics (HOS) based periodogram for iterative peak search and refinement to jointly estimate both range, velocity, and angle in the presence of unknown co-channel interferers. We further exploit constellation asymmetry to resolve the remaining phase ambiguities of blind recovery, enabling blind coherent demodulation via minimum constellation fitting. We also benchmark the performance through matched data-aided and stochastic Cramer-Rao lower bounds. We then quantify the cost of signal blindness. Simulations and experimental validations demonstrate reliable radar parameter estimation together with effective communication demodulation even when the TF-domain link is severely interfered with.

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