## 5 Simulation Experimental Results  
Compared with a two-channel or multichannel spaceborne SAR system, such as the Italian COSMO-SkyMed [40], the German TerraSAR-X [11; 12; 13; 14], and the Canadian Radarsat-2 [27], the distributed SAR systems provide the possibility to detect slowly moving targets based on large along-track baselines and enhance the moving target velocity estimation accuracy based on multiple baselines. Satellite formation, radar system and raw data simulation, and SAR-GMTI signal processing are the crucial problems to verify distributed spaceborne SAR system design and analyze signal processing technique performance. The SBRAS is an economical software developed by our lab [15; 22; 23; 24; 25], and the capabilities include satellites simulation, radar system simulation, SAR raw data simulation, monostatic/bistatic/multistatic SAR imaging, InSAR (interferometric synthetic aperture radar) processing, Digital Elevation Model (DEM) generation, GMTI/SAR-GMTI signal processing, system and signal processing performance analysis, and many other functions. The main SAR-GMTI simulation flow chart based on SBRAS is shown in Figure 5. To verify the above clutter suppression and moving target detection algorithm, some simulation experiments and analyses are developed on SBRAS [15; 22; 23; 24; 25]. The multistatic SAR images, which include moving targets, are simulated based on SBRAS. We use the proposed method to the clutter cancellation, moving target detection, target relocation, and performance analysis. The simulated SAR image, the interferometric phase map derived from the road database, and azimuth displacement map are presented in Figure 6. The simulation parameters are: satellite speed \(v_{s}=7.5\) Km/s, altitude \(H=514\) Km, the number of satellites \(K=6\), antenna size (length \(\times\) width) \(7\) m \(\times\) 0.5 m, wavelength \(\lambda=0.0563\) m, \(PRF=2.9\) kHz, chirp bandwidth \(BW=50\) MHz, incidence angle \(\theta_{inc}=30^{0}\), and pulse width \(PW=35\) us. The satellites fly on the SAR-Train formation with uniform along-track baseline \(B=150\) m.  
The master satellite does both transmit and receive, while other slave satellites only receive the radar echo. The simulated static scene is composed of several fields with different kinds of mean RCS, which include trees, buildings, roads, and so on. Additionally, there are eighteen simulated targets driving along the road, which are modeled as point targets. Figure 5(a) shows the simulated master satellite SAR image. In Figure 5(a), the moving targets are buried within the clutter, which cannot be directly detected. Figure 5(b) shows the road map, which is derived from the road network database and the master satellite SAR image. In Figure 5(c), the interferometric phase map is derived according to Equations (12)-(14), which only shown within \([-pi,+pi]\) to see with ease. In Figure 5(d), the azimuth displacement map can also be derived from Equations (12)-(14) pixel by pixel, which also only show within small range corresponding to the interferometric phase map. For the proposed MHT technique, the entire phase map and displacement map should be applied to steering vector estimation and clutter suppression. Figure 5: Distributed spaceborne SAR-GMTI simulation flow chart. Figure 6: _Cont._  
The SAR-GMTI signal processing simulation results are shown in Figure 7, in which the simulation static scene, satellites, and radar parameters are the same as in Figure 6. Some SAR-GMTI signal processing steps, which include monostatic/bistatic SAR imaging, coregistration, and channel balance, exploited the techniques developed on SBRAS. In the simulations of Figure 7, the proposed MHT technique uses the AMF statistic for computational considerations. Figure 7a shows the real positions (or priori positions) as the \"red dots\" of the eighteen simulated moving targets.