1. Field of the Invention
The present invention relates generally to a method and system for manipulating, formatting, and subsequently processing synthetic aperture radar (SAR) data and other coherent signal data into complex imagery with image resolution and geometric accuracy commensurate with the inherent information content of the data. More particularly, the present invention relates to a method and system for providing along-track alignment and formatting of coherent SAR data in which such method and system manipulate the coherent SAR data in order to align and format signals from individual scatterers to achieve an ideal data storage format in the along-track dimension.
2. Background Art
Image formation processors generate images from scenes sensed by synthetic aperture radar (SAR) sensors. A SAR sensor transmits electromagnetic signals such as pulses towards a scene while the SAR sensor is moving with respect to the scene. The SAR sensor receives a portion of the transmitted signal which has been reflected from a scatterer in the scene back towards the SAR sensor. An image formation processor analyzes data indicative of the reflected signal portions received by the SAR sensor from the scatterers in the scene in order to generate an image representative of the scene.
Data formatting is an important element in the performance of a fine resolution SAR image formation processor. SAR image formation processors attempt to format the incoming data indicative of the reflected signal portions and the movement of the SAR sensor in various ways in order to optimize the success of the signal processing and image formation operations. The objective of data format operations within a SAR image formation algorithm is to establish the data appropriately in a wavenumber or spatial frequency domain (KX, KY) such that a subsequent two-dimensional (2d) Fourier transform yields undistorted diffraction- limited imagery of complex three-dimensional scenes.
Current SAR image formation algorithms include the rectangular format algorithm (RFA), the polar format algorithm (PFA), the range migration algorithm (RMA), the chirp scaling algorithm (CSA), and the frequency scaling algorithm (FSA). The RFA, the PFA, and the RMA, in order, offer a progression from a simplistic format to an ideal format; from limited scene size and image quality to large seamless images at excellent image quality; and from minimum computational cost to an often-excessive computational burden. CSA and FSA are attempts to reduce the complexity and/or computational burden of RMA at the expense of image quality.
The way in which each SAR image formation algorithm addresses data formatting defines the nature of the algorithm and affects its area of applicability, its limitations, and its computational complexity. Often, it is computational complexity that drives the search for improvements in a SAR image formation algorithm that already provides satisfactory image quality. This search typically involves a tradeoff between image quality and computational burden. Another consideration is the ease of implementation. The RFA operates with minimum need for auxiliary data and minimum sensitivity to its accuracy. However, the RFA formats the data properly in neither range nor azimuth; the PFA requirements are moderate, well understood and manageable. It formats the data properly only from scene center; the RMA formats the data properly in both range and azimuth from all target locations.
The RMA is potentially the ideal algorithm for fine-resolution SAR imaging of large scenes in the most challenging data collection environments. A disadvantage of the RMA is that the RMA must operate on azimuth chirped signal data. That is, the starting point of the RMA is a signal history with data stabilization to a sliding reference point (that is, data stabilization to a line). For SAR systems in which the azimuth extent of a processed image is smaller than the synthetic aperture length required to achieve the desired azimuth resolution, this starting point leads to an unnecessarily high along-track sampling rate at the front-end of the RMA processor because the total Doppler bandwidth (required for azimuth resolution) is larger than the azimuth-dechirped scene bandwidth in these cases. For some imaging geometries (in particular, ultrawide-angle strip map and fine-resolution spotlight imaging), excess azimuth sampling on the order of 10:1 or higher may be necessary. Such large over-sampling of signal history data represents a large computational burden on the image formation processor.
Additionally, the RMA requires a one-dimensional (range) precision interpolation which is known as the Stolt interpolation. The RFA requires no interpolation; and the PFA requires both an azimuth interpolation and a range interpolation. Both the CSA and the FSA follow the RMA in azimuth, but trade image quality to avoid the need for even the Stolt interpolation in range.