Sparse Bayesian Learning Based Three-Dimensional Imaging Algorithm for Off-Grid Air Targets in MIMO Radar Array
Abstract
:1. Introduction
2. Problem Formulation of 3D Imaging
2.1. Ideal Imaging Model Based on Sparse Antenna Array
2.2. Off-Grid Imaging Model Using Taylor Expansion
3. The Proposed Off-Grid Imaging Algorithm
3.1. Algorithm Description
3.1.1. The Three-Stage Sparse Prior Model
3.1.2. Variational Inference EM Based Sparse Recovery Algorithm
3.2. Bayesian Cramér-Rao Bounds For Off-Grid Biases
4. Experimental Results
4.1. Validation of The Proposed Algorithm
4.2. Super-Resolution Performance Versus SNR
4.3. BCRB for Off-Grid Biases
5. Conclusions
Author Contributions
Conflicts of Interest
References
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Processing Steps of the Off-Grid Imaging Method. |
---|
Input: |
Initialization: |
, , , , |
Iteration: let i denotes the iteration counter |
(1) update by Equation (30) |
(2) update by Equation (32) |
(3) update by Equation (34) |
(4) update by Equation (36) |
(5) update and by Equations (37) and (39) |
Termination condition: |
The iteration ends when . |
Output: |
The imaging result , the off-gird bias estimation and |
Parameter | Symbol | Value |
---|---|---|
Bandwidth | B | 500 MHz |
Carrier frequency | 10 GHz | |
Baseline in the X-direction | 6 m | |
Baseline in the Y-direction | 6 m | |
Target range | R | 2500 m |
Pulse width | 10 s | |
Number of transmitters | M | 4 |
Number of receivers | N | 225 |
Algorithm | OMP | BP | S-TLS | OGSBI | Proposed Method |
---|---|---|---|---|---|
NMSE of | 1.3371 | 1.1129 | 0.6921 | 0.5397 | 0.3016 |
NMSE of | * | * | 0.6048 | 0.2452 | 0.1333 |
NMSE of | * | * | 0.6321 | 0.2283 | 0.1266 |
OGSBI, SNR = 10 dB | 0.0064 | 0.9932 | 0.5682 | 0.0490 |
OGSBI, SNR = 20 dB | −0.0064 | 0.9949 | 0.2857 | 0.0412 |
Proposed method, SNR = 10 dB | 0.0014 | 0.9948 | 0.4726 | 0.0418 |
Proposed method, SNR = 20 dB | −0.0080 | 0.9975 | 0.2553 | 0.0435 |
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Share and Cite
Jiao, Z.; Ding, C.; Liang, X.; Chen, L.; Zhang, F. Sparse Bayesian Learning Based Three-Dimensional Imaging Algorithm for Off-Grid Air Targets in MIMO Radar Array. Remote Sens. 2018, 10, 369. https://doi.org/10.3390/rs10030369
Jiao Z, Ding C, Liang X, Chen L, Zhang F. Sparse Bayesian Learning Based Three-Dimensional Imaging Algorithm for Off-Grid Air Targets in MIMO Radar Array. Remote Sensing. 2018; 10(3):369. https://doi.org/10.3390/rs10030369
Chicago/Turabian StyleJiao, Zekun, Chibiao Ding, Xingdong Liang, Longyong Chen, and Fubo Zhang. 2018. "Sparse Bayesian Learning Based Three-Dimensional Imaging Algorithm for Off-Grid Air Targets in MIMO Radar Array" Remote Sensing 10, no. 3: 369. https://doi.org/10.3390/rs10030369
APA StyleJiao, Z., Ding, C., Liang, X., Chen, L., & Zhang, F. (2018). Sparse Bayesian Learning Based Three-Dimensional Imaging Algorithm for Off-Grid Air Targets in MIMO Radar Array. Remote Sensing, 10(3), 369. https://doi.org/10.3390/rs10030369