研究目的
To design a moving target detection scheme for terahertz SAR systems based on multilook processing, leveraging the sensitivity of THz SAR to Doppler vibration for improved detection performance, especially for slow-moving targets.
研究成果
The proposed multilook processing algorithm effectively detects moving targets in THz SAR systems by exploiting Doppler sensitivity, with simulated results showing successful detection, particularly for slow-moving targets. This approach enhances SAR capabilities for security and industrial applications, suggesting potential for future real-world implementation and further refinement.
研究不足
The study is based on simulated data, which may not fully capture real-world complexities and noise. The algorithm's performance in practical THz SAR systems with actual environmental factors and hardware limitations is not tested. Optimization for different target speeds or scenarios is not explored.
1：Experimental Design and Method Selection:
The study uses a multilook processing technique in the Doppler domain for THz SAR systems. After range compression, azimuth FFT is applied to transform signals into the range-Doppler domain. The Doppler spectrum is divided into sub-looks, and azimuth compression is applied separately to generate sub-images. Moving targets are detected by comparing the sharpness of these sub-images, as stationary targets remain identical while moving targets differ due to Doppler shifts.
2：Sample Selection and Data Sources:
Simulated THz SAR data is used, with two targets in the scene: one moving with a radial velocity of 1.5 m/s and one stationary, based on the geometry shown in Fig.
3：5 m/s and one stationary, based on the geometry shown in Fig. List of Experimental Equipment and Materials:
3.
3. List of Experimental Equipment and Materials: No specific physical equipment is mentioned; the experiment is conducted using simulated data with parameters listed in Table I (e.g., carrier frequency 225 GHz, platform velocity 100 m/s).
4：Experimental Procedures and Operational Workflow:
Range compression is performed first, followed by azimuth FFT to obtain range-Doppler signals. The Doppler spectrum is divided into parts (e.g., two sub-looks), and azimuth compression is applied to each sub-look to produce sub-images. Sharpness comparison between sub-images is used to detect moving targets.
5：Data Analysis Methods:
Analysis involves visual inspection and comparison of azimuth profiles from sub-images (as shown in Fig. 2) to identify differences indicating moving targets. No specific statistical techniques or software tools are detailed.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
