Desktop version

Home arrow Engineering arrow Study on Ground Moving Target Indication and Imaging Technique of Airborne SAR

Simulation and Raw Data Processing

In the simulation, one moving target with inconstant cross-track velocity is set at the center of the scene according to the system parameters listed in Table 3.1. The average cross-track velocity of the moving target is 10 m/s, whereas its actual cross-track velocity varies during Ta as shown in Fig. 6.11a. The platform velocity is not constant during Ta either, and it is shown in Fig. 6.11b. The proposed motion error compensation algorithm is implemented to estimate and correct the motion error of the moving target.

The platform velocity error is firstly compensated with INS data. According to our cross-track velocity error estimation algorithm, a reference signal with the cross-track velocity of 10 m/s is simulated, and the time-frequency distributions of the moving target and the reference target are shown in Fig. 6.11c. Together with Fig. 6.11a, it can be noted that the time-frequency distribution accurately reflects the changes of the cross-track velocity. The estimated velocity error is shown in Fig. 6.11d. We can see that the actual cross-track velocity of the moving target is correctly estimated by our algorithm. The imaging results of the moving target before and after the compensation are compared in Fig. 6.11e, f. The image of the moving target splits into several peaks as shown in Fig. 6.11e, which indicates that

Flowchart of the proposed moving target processing strategy. MOCO represents motion error compensation

Fig. 6.10 Flowchart of the proposed moving target processing strategy. MOCO represents motion error compensation

the moving target has more than one Doppler centroid. After the compensation, the imaging resolution is significantly improved, as shown in Fig. 6.11f.

The same Ku-band real airborne SAR data is used to prove the effectiveness of this algorithm. Here, we use T2 as an example to testify the performance of the proposed motion error compensation algorithm in the real data processing.

The time-frequency distributions of the moving target and the reference target are shown in Fig. 6.12a. The imaging results before and after the compensation are compared in Fig. 6.12b. We can see from Fig. 6.12b that the imaging resolution is significantly improved after the compensation.

The final imaging result of the seven moving targets with the proposed moving target processing strategy is shown in Fig. 6.13. All the moving targets (tagged by arrows and rectangles) are detected by the proposed strategy, and they are also focused and relocated to their actual locations. Therefore, the effectiveness of the proposed strategy in the real data processing is confirmed.

The processing results of motion error compensation

Fig. 6.11 The processing results of motion error compensation. a Actual cross-track velocity, b Actual platform velocity, c Time-frequency distribution of the moving target, d Result of the cross-track velocity estimation, e Imaging before the motion error compensation, f Imaging after the motion error compensation

Results of the motion error compensation. a Time-frequency distributions of T2 and the reference signal. b Imaging comparison of T2 before and after the motion error compensation

Fig. 6.12 Results of the motion error compensation. a Time-frequency distributions of T2 and the reference signal. b Imaging comparison of T2 before and after the motion error compensation

Imaging of the moving targets in the stationary image with the proposed strategy

Fig. 6.13 Imaging of the moving targets in the stationary image with the proposed strategy

 
Source
< Prev   CONTENTS   Source   Next >

Related topics