Air- and spaceborne monitoring of road traffic using SAR moving target indication—Project TRAMRAD

A Performance Evaluation of SAR-GMTI Missions for Maritime Applications

“…It is well-known that the target radar cross section (RCS) varies with the aspect angle [25]. For the deterministic target model the different scattering centers are assumed to have a constant radar response during the integration time, such that for calibrated images, α t is directly related to the square root of the RCS.…”

“…The term ∆ AT I (ϑ t ) collects the along-track phase change for the different channels at the displaced image position of the moving target. As it is extendedly considered in literature [23]- [25], x 0 = 0 is assumed for simplicity in the mathematical notation without losing generality. Then, the interferometric phase component of the i-th channel can be expressed as [23] ∠…”

“…Therefore, for the main non-ambiguous clutter patch, a grid of N surrounding ambiguous clutter responses should be also considered when modeling the clutter [14], [18], [25]. Assuming a homogeneous (stationary) complex Gaussian sea clutter surface and uncorrelated ambiguities, the interference covariance matrix can be expressed as:…”

“…As modeled in section II-B, and noted in [14] and [25], the contribution of the ambiguous clutter returns should be taken into consideration as they could play an important role in the SAR-GMTI performance: the residual coregistration error on the ambiguities, as denoted by the second term in (10), when the DPCA condition does not hold, produces additional eigenvalues different from the noise floor, and therefore more RX channels are required to cancel out both unambiguous and ambiguous clutter patches, [19]. Moreover, temporal decorrelation of the sea clutter returns, present also in the ambiguous patches, could produce additional eigenvalues different from noise floor.…”

Extraction and motion estimation of vehicles in single-pass airborne LiDAR data towards urban traffic analysis

“…Traffic monitoring remains as one of the few fields which are still not as intensively analyzed in the LiDAR community compared to other modern sensor techniques such as frame and linear optical cameras (Zhao and Nevatia, 2003;Eikvil et al, 2009;Hinz et al, 2008;Larsen et al, 2009), Synthetic Aperture Radar (SAR) (Meyer et al, 2006;Bethke et al, 2006), and infrared (IR) cameras (Kirchhof and Stilla, 2006;Yao et al, 2009). The most relevant research to our work came from Toth and Grejner-Brzezinska (2006).…”