Publications

The MATLAB language has become a standard for rapid prototyping throughout all disciplines of engineering because the environment is easy to understand and use. Many of the basic functions included in MATLAB are those operations that are necessary to carry out larger algorithms such as the chirp z-transform spectral zoom. These functions include, but are not limited to mathematical operators, logical operators, array indexing, and the Fast Fourier Transform (FFT). However, despite its ease of use, MATLAB's technical computing language is interpreted and thus is not always capable of the memory management and performance of a compiled language. There are however, several optimizations that can be made within the chirp z-transform spectral zoom algorithm itself, and also to the MATLAB implementation in order to take full advantage of the computing environment and lower processing time and improve memory usage. To that end, this document's purpose is two-fold. The first demonstrates how to perform a chirp z-transform spectral zoom as well as an optimization within the algorithm that improves performance and memory usage. The second demonstrates a minor MATLAB language usage technique that can reduce overhead memory costs and improve performance.

Traditional polar format image formation for Synthetic Aperture Radar (SAR) requires a large amount of processing power and memory in order to accomplish in real-time. These requirements can thus eliminate the possible usage of interpreted language environments such as MATLAB. However, with trapezoidal aperture phase history collection and changes to the traditional polar format algorithm, certain optimizations make MATLAB a possible tool for image formation. Thus, this document's purpose is two-fold. The first outlines a change to the existing Polar Format MATLAB implementation utilizing the Chirp Z-Transform that improves performance and memory usage achieving near realtime results for smaller apertures. The second is the addition of two new possible image formation options that perform a more traditional interpolation style image formation. These options allow the continued exploration of possible interpolation methods for image formation and some preliminary results comparing image quality are given.

SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processing through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.