[Paper Review] Adaptive detection and localization exploiting the IEEE 802.11ad standard

Emanuele Grossi, Marco Lops+1 more|arXiv (Cornell University)|Apr 29, 2019

Radar Systems and Signal ProcessingEngineering71 references45 citations

TL;DR

This paper proposes an adaptive radar detection and localization method exploiting the sector-level sweep (SLS) phase of the IEEE 802.11ad 60 GHz standard for opportunistic sensing. By sequentially detecting and canceling stronger targets, the method overcomes signal spillover and near-far problems from the probing signal's imperfect auto-correlation, achieving detection and localization performance close to single-target benchmarks with sub-centimeter accuracy in multi-target scenarios.

ABSTRACT

In this work, we exploit the sector level sweep of the IEEE 802.11ad communication standard to implement an opportunistic radar at mmWaves and derive an adaptive procedure for detecting multiple targets (echoes) and estimating their parameters. The proposed detector/estimator extracts the prospective echoes one-by-one from the received signal, after removing the interference caused by the previously detected (stronger) targets. Examples are provided to assess the system performance, also in comparison with the canonical matched-filter peak-detector and the Cram\'er-Rao bounds. Results indicate that the proposed method is robust against the signal spillover and the near-far problem caused by the imperfect auto-correlation of the probing signal and, for the same probability of false alarm, grants detection and localization performances close to those previously obtained in a simplified single-target scenario.

Motivation & Objective

• To address the limitations of conventional matched-filter peak detection in multi-target mmWave radar using IEEE 802.11ad.
• To overcome signal spillover and near-far effects caused by the non-ideal auto-correlation of the CPHY preamble.
• To enable robust, adaptive detection and localization of multiple targets in short-range environments using existing communication signals.
• To achieve performance close to theoretical limits (Cramér-Rao bounds) under realistic multi-target conditions.

Proposed method

• The proposed method uses an adaptive multi-target detector that processes the SLS signal sequentially, detecting the strongest target first.
• It applies interference cancellation by subtracting the estimated echo of each detected target from the received signal before processing the next.
• A refined estimator is applied to improve range accuracy, achieving sub-centimeter resolution.
• The method leverages the known structure of the IEEE 802.11ad CPHY preamble, including Golay sequences and preamble structure, for signal modeling.
• A detection threshold is set based on the desired probability of false alarm (Pfa), and the process is repeated iteratively.
• The approach is evaluated using a processing window of 512 symbol intervals, balancing performance and computational cost.

Experimental results

Research questions

• RQ1 Can an opportunistic radar using IEEE 802.11ad SLS achieve reliable detection and localization in multi-target environments despite signal spillover?
• RQ2 How does the adaptive interference cancellation scheme perform compared to a canonical matched-filter peak detector in the presence of strong and weak targets?
• RQ3 What is the achievable range and amplitude estimation accuracy under realistic signal conditions and multiple targets?
• RQ4 How does the processing window length and time delay resolution (∆g) affect target resolution and detection performance?
• RQ5 To what extent does the proposed method approach the theoretical performance limits (Cramér-Rao bounds) in multi-target scenarios?

Key findings

• The proposed adaptive method achieves detection and localization performance within 1-2 dB of the single-target scenario for the same Pfa, demonstrating robustness to interference.
• With a 512-symbol processing window, the method achieves a detection probability >0.8 up to 25 m for targets with 0.1 m² RCS.
• Range estimation accuracy reaches a few centimeters, improving to a few millimeters with the refined estimator at shorter ranges.
• Reducing the time delay resolution ∆g from T to T/8 improves range resolution by approximately 8.5 cm, enabling better separation of closely spaced targets.
• When target separation drops below 8.5 cm, the RMSE degrades due to mutual interference but improves again as targets merge into a single effective scatterer.
• The method effectively mitigates false detections and target masking caused by signal spillover, outperforming the canonical matched-filter peak detector in multi-target scenarios.