11.07.2015 Views

Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

SHOW MORE
SHOW LESS
  • No tags were found...

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

268 CHAPTER 7 Stripmap SARTABLE 7-1Survey <strong>of</strong> SAR Image Formation AlgorithmsCategory Features Limitations Algorithms NotesDoppler Requires only a 1-D No accounting for Doppler beam Fourier transform provides thefast Fourier transform migration <strong>of</strong> scatterers sharpening (DBS) matched filter(FFT) after pulse through range bins DBS with Accounts for quadratic phase error (QPE)compression or phase orders azimuth dechirp by applying a conjugate quadraticabove linearmodulation to the data prior to DBSFourier Match filtering with the Data acquisition must Range-Doppler Assumes a single PSR is goodmatched point spread response be linear with uniform algorithm for the entire scene, s<strong>of</strong>ilter (PSR) implemented spacing between focused swath depth is limitedefficiently by along-track samples Range migration Range Doppler algorithm combinedmultiplication in the algorithm (RMA) with Stolt data interpolation providesfrequency domainerror-free imaging over deep swathsChirp scalingalgorithmRange stackingalgorithmExploits direct sampling <strong>of</strong> linearfrequency modulated (LFM) waveformsto realize a computationally efficientapproximation to the Stolt interpolationLike RMA, but less computationallyefficientTomo- Projection-slice view Scene size; data must Rectangular Analogous to DBS in simplicity;graphic <strong>of</strong> data acquisition; be time delayed and formatting capable <strong>of</strong> fine resolution, butefficient image phase corrected prior algorithm scene size severely restrictedformation follows to image formation Polar formatting 2-D data interpolation provides qualityalgorithm imaging at fine resolutions overreasonable scene sizes; scene extentsultimately limited by geometricconsiderationsInverse A more holistic, Demanding processing Matched filtering Employs a product <strong>of</strong> the data and amathematical view <strong>of</strong> requirements, and reference response; implementabledata acquisition and sometimes memory in either time-distance or frequencyimage formation requirements as well domainsConstant aperture Delay and sum imaging; same databackprojection records used for all pixelsConstant Like constant aperture backprojection,integration anglebackprojectionFilteredbackprojectionFastbackprojectionQuad-treeConstrainedinversionbut different subset <strong>of</strong> the overalldata applied to each pixel to realizea constant integration angleWideband/wide-angle data arepreequalized to improve impulseresponse in the final imageFamily <strong>of</strong> algorithms that garnercomputational efficiencies by makingminor approximations to basicbackprojectionFast backprojection usingmultiresolution topologiesSAR imaging treated as amathematical inverse problem

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!