MM-2FSK: Multimodal Frequency Shift Keying for Ultra-Efficient and Robust High-Resolution MIMO Radar Imaging

TL;DR

This paper introduces MM-2FSK, a multimodal radar imaging method that combines optical depth sensing with frequency shift keying to achieve high-resolution 3D imaging of dynamic targets efficiently.

Contribution

The paper presents a novel multimodal approach that integrates optical depth sensing with FSK radar to enable high-resolution, fast, and resource-efficient 3D imaging of moving targets.

Findings

Superior depth quality compared to traditional single-frequency methods

Achieves high framerate capture with limited frequencies

Competitively matches multi-frequency measurements in accuracy

Abstract

Accurate reconstruction of static and rapidly moving targets demands three-dimensional imaging solutions with high temporal and spatial resolution. Radar sensors are a promising sensing modality because of their fast capture rates and their independence from lighting conditions. To achieve high spatial resolution, MIMO radars with large apertures are required. Yet, they are infrequently used for dynamic scenarios due to significant limitations in signal processing algorithms. These limitations impose substantial hardware constraints due to their computational intensity and reliance on large signal bandwidths, ultimately restricting the sensor's capture rate. One solution of previous work is to use few frequencies only, which enables faster capture and requires less computation; however, this requires coarse knowledge of the target's position and works in a limited depth range only. To address these challenges, we extend previous work into the multimodal domain with MM-2FSK, which leverages an assistive optical depth sensing modality to obtain a depth prior, enabling high framerate capture with only few frequencies. We evaluate our method using various target objects with known ground truth geometry that is spatially registered to real millimeter-wave MIMO radar measurements. Our method demonstrates superior performance in terms of depth quality, being able to compete with the time- and resource-intensive measurements with many frequencies.