Abstract
Ground-based (GB) radar is an effective approach in lunar observation. In GB radar lunar three-dimensional (3D) high-resolution imaging, orbital measurement error will degrade the image quality, and should be estimated and compensated. In this manuscript, an orbit error estimation and compensation method for GB radar lunar 3D imaging based on minimum entropy is proposed. First, echo model considering orbit error is established. Thereafter an autofocus algorithm based on back projection and minimum entropy is proposed to acquire fine-resolved image. Furthermore, particle swarm optimization (PSO) algorithm based on dynamic inertia weight is used to estimate the optimal compensation parameter to minimize the image entropy. Finally, computer simulation results validate the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 4173-4177 |
| Number of pages | 5 |
| Journal | IET Conference Proceedings |
| Volume | 2023 |
| Issue number | 47 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | IET International Radar Conference 2023, IRC 2023 - Chongqing, China Duration: 3 Dec 2023 → 5 Dec 2023 |
Keywords
- GROUND-BASED (GB) RADAR
- LUNAR THREE DIMENSIONAL (3D) IMAGING
- MINIMUM ENTROPY
- ORBIT ERROR ESTIMATION AND COMPENSATION
- PARTICLE SWARM ALGORITHM (PSO)