Related Experiment Video
Updated: Aug 5, 2026
15:25
Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
Published on: February 4, 2018
System-Level Hardware-Waveform Co-Design for Micro-UAV Radar Sensors: Suppressing Noise Folding in Extreme SWaP-C
Xinhua Dai1, Kai Xie1, Youkang Wang1
1School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen Campus, No. 66 Gongchang Road, Guangming District, Shenzhen 518107, China.
Sensors (Basel, Switzerland)
|July 28, 2026
Summary
This study introduces a new Spread Spectrum Digital Beamforming (SSDBF) design for micro-UAV radar, significantly reducing noise and improving detection range. The novel approach optimizes hardware-waveform co-design under strict Size, Weight, Power, and Cost constraints.
Area of Science:
- Electrical Engineering
- Radar Systems
- Signal Processing
Background:
- Micro-Unmanned Aerial Vehicles (micro-UAVs) face stringent Size, Weight, Power, and Cost (SWaP-C) constraints for compact radar arrays.
- Spread Spectrum Digital Beamforming (SSDBF) offers hardware reduction but suffers from noise folding and transient injection due to receiver switching.
Purpose of the Study:
- To develop a hardware-waveform co-design framework for SSDBF systems to mitigate noise issues.
- To optimize bipolar spreading sequences for reduced transition density and improved radar performance under SWaP-C constraints.
Main Methods:
- Developed a framework linking bipolar spreading sequence transition density to high-frequency code energy and switching events.
- Utilized transition density as a design surrogate for folded noise, constrained with non-zero-shift cross-correlation.
- Proposed an ϵ-constrained Greedy Coordinate Space Search (ϵ-GCSS) algorithm to synthesize low-transition-density SSDBF code sets.
Main Results:
- Reduced transition density from ~0.50 to ~0.19 compared to PRN-like codes.
- Lowered integrated IF noise power by 9.63 dB.
- Improved normalized maximum detection range by 8.2 percentage points at K=4.
Conclusions:
- The proposed SSDBF code set effectively reduces noise and enhances detection range for micro-UAV radar systems.
- The hardware-waveform co-design framework provides a viable solution for optimizing radar performance within SWaP-C limitations.
- The ϵ-GCSS algorithm successfully synthesizes efficient SSDBF code sets without additional analog front-end hardware.