New algorithm enhances Doppler resolution of unmanned vehicle radars

A research team has developed an extrapolation-based Doppler resolution enhancement algorithm for frequency modulated continuous wave radars. The algorithm improves system performance, offering an advancement that is superior to existing ultra-high-resolution technologies.

The findings are published in the Journal of Electrical Engineering & Technology. The team was led by Sang-dong Kim and Bong-seok Kim, affiliated with the DGIST Division of Mobility Technology, in collaboration with a team led by Professor Youngdoo Choi, affiliated with the Republic of Korea Naval Academy (ROKNA).

Improving radar accuracy without extra hardware

This research introduces a technology that improves radar detection accuracy without the need for additional complex computations or hardware. The technology is expected to contribute to enhancing radar system performance on various intelligent unmanned platforms such as unmanned aerial vehicles (UAVs), unmanned ships, and autonomous vehicles.

Conventional radar systems analyze the Doppler effect to determine the velocity of a target, but the fast Fourier transform (FFT)-based approach has limitations regarding resolution (i.e., the accuracy of velocity discrimination). To address this, the joint DGIST–ROKNA research team applied a signal extrapolation technique and has proposed a new algorithm that enhances Doppler resolution without extending observation time.

Performance gains and real-world applications

The proposed method successfully reduces the root mean square error of velocity estimation by up to 33% and decreases the target miss rate by up to 68%, representing a substantial improvement over the conventional approach. Notably, the proposed method maintains the same computational complexity level as the conventional FFT method, thereby simultaneously achieving fast processing speed and high efficiency.

This technology can effectively solve the problem of signal overlap between targets moving at similar velocities, particularly when UAVs or radar systems detect multiple objects simultaneously. It can therefore greatly enhance the ability to distinguish closely spaced targets and improve detection accuracy, marking a new milestone in the advancement of high-resolution target detection technology.

Additionally, the technology is highly regarded for its industrial applicability because it requires no additional hardware resources and features a simple computational structure that enables real-time implementation.

Sang-dong Kim, principal researcher at the Division of Mobility Technology (concurrently serving the interdisciplinary engineering major), said, “This study demonstrates an improvement in both the efficiency and precision of radar signal processing, enabling more accurate target detection without the need for additional equipment. It is expected to evolve into a key technology for defense, autonomous driving, and unmanned systems.”