Frank H. Wong

Precision SAR processing using chirp scaling

A space-variant interpolation is required to compensate for the migration of signal energy through range resolution cells when processing synthetic aperture radar (SAR) data, using either the classical range/Doppler (R/D) algorithm or related frequency domain techniques. In general, interpolation requires significant computation time, and leads to loss of image quality, especially in the complex image. The new chirp scaling algorithm avoids interpolation, yet performs range cell migration correction accurately. The algorithm requires only complex multiplies and Fourier transforms to implement, is inherently phase preserving, and is suitable for wide-swath, large-beamwidth, and large-squint applications. This paper describes the chirp scaling algorithm, summarizes simulation results, presents imagery processed with the algorithm, and reviews quantitative measures of its performance. Based on quantitative comparison, the chirp scaling algorithm provides image quality equal to or better than the precision range/Doppler processor. Over the range of parameters tested, image quality results approach the theoretical limit, as defined by the system bandwidth. >

A Two-Dimensional Spectrum for Bistatic SAR Processing Using Series Reversion

This letter derives the two-dimensional point target spectrum for an arbitrary bistatic synthetic aperture radar configuration. The method described makes use of series reversion, the method of stationary phase, and Fourier transform pairs to derive the point target spectrum. The accuracy of the spectrum is controlled by keeping enough terms in the two series expansions, and is verified with a point target simulation

Processing of Azimuth-Invariant Bistatic SAR Data Using the Range Doppler Algorithm

This paper discusses bistatic synthetic aperture radar processing (complex image formation) using the Range Doppler Algorithm. The key step is to use an analytical form of the signal spectrum derived by the method of series reversion. The spectrum is used for secondary range compression (SRC), range cell migration correction, and azimuth compression. The algorithm is able to focus the azimuth-invariant bistatic configuration where the transmitter and receiver platforms are moving in parallel tracks with identical velocities. Moreover, the algorithm is able to handle reasonably high squints and wide apertures because SRC can be performed in the 2-D frequency domain.

Focusing Bistatic SAR Data Using the Nonlinear Chirp Scaling Algorithm

Bistatic synthetic aperture radar data are more challenging to process than the common monostatic counterparts because the flight geometry is more complicated and the data are usually nonstationary. Whereas time-domain algorithms can handle general bistatic cases, they are very inefficient; therefore, frequency-domain methods are preferred. Several frequency-domain monostatic algorithms have been modified to handle a limited number of bistatic cases, but a general algorithm is sought, which can handle cases such as nonequal platform velocities, nonparallel flight tracks, and high squints. In this paper, we modify the nonlinear chirp scaling (NLCS) algorithm to handle a general case of bistatic data. The key is to use a linear range cell migration correction to reduce the range-azimuth coupling, an NLCS to precondition the data for azimuth compression, and a series expansion to obtain an accurate form of the signal spectrum. The azimuth nonstationarity is handled through the use of invariance regions. Simulations have shown that the modified NLCS algorithm can handle data with more complicated bistatic geometries than the previous algorithms.

A combined SAR Doppler centroid estimation scheme based upon signal phase

This paper describes a complete end-to-end Doppler centroid estimation scheme, which determines the fractional PRF part of the Doppler centroid. It also resolves the Doppler ambiguity. Experiments show that the scheme works successfully over various terrain types, including land, water, and ice, and that it requires only a modest amount of SAR data to perform reliably. The proposed scheme has an added advantage that it is directly applicable to RADARSAT and ENVISAT ScanSAR data. The scheme uses two complementary Doppler estimation algorithms, both utilizing the phase information embedded in the radar signal. In each algorithm, upper and lower parts of the available bandwidth of the received signal are extracted to form two range looks. The first algorithm, called multilook cross correlation (MLCC), computes the average cross correlation coefficient between adjacent azimuth samples for each of the two looks and then takes the difference between the angles of the two coefficients. The Doppler ambiguity is determined from the angle difference. The fractional pulse repetition frequency (PRF) part is also determined from the cross correlation coefficients. In the second algorithm, called multilook beat frequency (MLBF), the two looks are multiplied together to generate a beat signal. The beat frequency is then estimated and the Doppler ambiguity determined from the beat frequency. The MLCC algorithm performs better with low contrast scenes while the MLBF works better with high contrast ones. Although each algorithm works well on its own with sufficient averaging, it is also possible to use quality measures to select the best result from either algorithm. In this way, scenes of different content or contrast can be handled reliably. This paper presents the analysis of the two algorithms, explaining why their performance is affected by scene contrast, which is confirmed by experimental results with ERS-1 and JERS-1 data.

A Comparison of Point Target Spectra Derived for Bistatic SAR Processing

The existence of a double hyperbola in the bistatic range equation makes it difficult to find an exact analytical solution for the 2D point target spectrum. Several approximate solutions for the spectrum have been derived and used to focus bistatic synthetic aperture radar data. In this paper, we establish the relationship between three independently derived bistatic point target spectra. The first spectrum is Loffelds bistatic formula, which consists of a quasi-monostatic and a bistatic phase term. The second spectrum makes use of Roccas smile operator, which transforms bistatic data in a defined configuration to a monostatic equivalent. The third spectrum is derived using a power series - called the method of series reversion (MSR). The MSR spectrum is the most general among the three. This paper shows that this spectrum can be reduced to the same formulation as the former two when certain conditions are met. In addition, a new approximate spectrum is derived using a Taylor series expansion about the two stationary phase points of the transmitter and receiver. We also give an alternative geometrical proof of the relationship between Roccas smile operator and Loffelds bistatic deformation term. The accuracies of the point target spectra are demonstrated using simulations of an X-band bistatic airborne radar with a fixed baseline.

A SAR Processing Algorithm With No Interpolation

Current SAR processing algorithms incorporate interpolators to perform key functions. It turns out that the interpolators are difficult to implement, and are one of the largest sources of error in the processing. In this paper, we introduce a new algorithm which eliminates the use of the interpolation operation, yet achieves accurate range migration correction over the full range swath. The algorithm can handle large apertures and large squints, and has noticeably better phase and geometry accuracy than current algorithms, even when the apertures and squints are high. The new algorithm is called the Differential Range Deramp - Frequency Domain (DRD-FD) Algorithm, because its key operation is to use the linear-FM property of the range chirp to differentially shift the range energy as a function of azimuth frequency, and then to do the remaining range cell migration correction in the two-dimensional frequency domain. In this paper, the new algorithm is described, and simulation results are given to demonstrate its focussing, phase and geometric performance with squinted SAR data. In addition, an image is shown made from SEASAT data.

Interpretations of the omega-K algorithm and comparisons with other algorithms

This paper presents a Fourier interpretation of the Omega-k SAR processing al- gorithm that helps explain the key Stolt mapping operation. An approximate form of the algorithm is sometimes used, and we explain how both forms of the ωKA compare with the range Doppler and the chirp scaling algorithms. Finally, a brief dis- cussion is given on which radar parameters allow the accurate use of each algorithm.

Processing simulated RADARSAT SAR data with squint by a high precision algorithm

A key step in the differential range deramp (DRD) algorithm in SAR processing is to use the linear-FM property of the range chirp to differentially shift the range energy as a function of azimuth frequency. The remaining bulk range cell migration correction (RCMC) can then be done in the two-dimensional frequency domain. When the azimuth FM rate parameter is range invariant, the deramp function is linear frequency modulated. In practice, this parameter is a function of range. The deramp function is modified to accommodate this range variance of the azimuth FM rate parameter. Experiments were performed with simulated RADARSAT SAR in realistic situations, and with squint. This paper focuses on presenting the experimental results.<<ETX>>

Phase-preserving processing of ScanSAR data with a modified range Doppler algorithm

Presents a phase-preserving algorithm for processing ScanSAR data, based on modifications to the well-known RD algorithm. The azimuth compression stage is modified to isolate each targets energy within the burst regimes. Analysis and simulations verify the phase accuracy of the modified algorithm.