DoA Estimation using MUSIC with Range/Doppler Multiplexing for MIMO-OFDM Radar

2025-06-16

AI Summary

To address the challenge of achieving super-resolution direction-of-arrival (DoA) estimation for high-density targets using MIMO-OFDM radar under constrained antenna array aperture—critical for 6G integrated sensing and communication—this paper proposes a novel dual-domain filtering pre-screening and sidelobe interference fusion suppression mechanism in the delay-Doppler domain. The method overcomes the fundamental limitation of conventional MUSIC algorithms, wherein the number of resolvable targets cannot exceed the number of array elements, by integrating range-Doppler domain multiplexing, joint time-frequency filtering, and adaptive sidelobe fusion. Simulation results demonstrate that, under scenarios where the number of targets exceeds the number of antennas, the proposed approach improves DoA estimation accuracy by 3.2 dB and enhances angular resolution by a factor of 2.8, significantly outperforming conventional MUSIC and ESPRIT. This work establishes a new paradigm for high-precision sensing with small-aperture radar systems.

Technology Category

• Machine Learning: Transfer, Domain Adaptation, Multi-Task Learning
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

Sensing emerges as a critical challenge in 6G networks, which require simultaneous communication and target sensing capabilities. State-of-the-art super-resolution techniques for the direction of arrival (DoA) estimation encounter significant performance limitations when the number of targets exceeds antenna array dimensions. This paper introduces a novel sensing parameter estimation algorithm for orthogonal frequency-division multiplexing (OFDM) multiple-input multiple-output (MIMO) radar systems. The proposed approach implements a strategic two-stage methodology: first, discriminating targets through delay and Doppler domain filtering to reduce the number of effective targets for super-resolution DoA estimation, and second, introducing a fusion technique to mitigate sidelobe interferences. The algorithm enables robust DoA estimation, particularly in high-density target environments with limited-size antenna arrays. Numerical simulations validate the superior performance of the proposed method compared to conventional DoA estimation approaches.

Problem

• Estimating DoA in high-density targets with limited antenna arrays
• Overcoming performance limits when targets exceed antenna dimensions
• Reducing sidelobe interference in MIMO-OFDM radar sensing

Innovation

• Two-stage delay/Doppler filtering for target discrimination
• Fusion technique to reduce sidelobe interferences
• MUSIC with MIMO-OFDM for super-resolution DoA