Abstract: Methods and apparatus compress data, comprising an In-phase (I) component and a Quadrature (Q) component. Statistical characteristics of the data are utilized to convert the data into a form that requires fewer bits in accordance with the statistical characteristics. The data may be further compressed by transforming the data and by modifying the transformed data in accordance with a quantization conversion table that is associated with the processed data. Additionally, redundancy may be removed from the processed data with an encoder. Subsequent processing of the compressed data may decompress the compressed data in order to approximate the original data by reversing the process for compressing the data with corresponding inverse operations. Interleaved I and Q components can be processed rather than separating the components before processing the data. The processed data type may be determined by providing metadata to retrieve the appropriate quantization table from a knowledge database.

Abstract: Methods and apparatus compress data, comprising an In-phase (I) component and a Quadrature (Q) component. Statistical characteristics of the data are utilized to convert the data into a form that requires fewer bits in accordance with the statistical characteristics. The data may be further compressed by transforming the data and by modifying the transformed data in accordance with a quantization conversion table that is associated with the processed data. Additionally, redundancy may be removed from the processed data with an encoder. Subsequent processing of the compressed data may decompress the compressed data in order to approximate the original data by reversing the process for compressing the data with corresponding inverse operations. Interleaved I and Q components can be processed rather than separating the components before processing the data. The processed data type may be determined by providing metadata to retrieve the appropriate quantization table from a knowledge database.

Abstract: Methods and apparatus compress data, comprising an In-phase (I) component and a Quadrature (Q) component. The compressed data may be saved into a memory or may be transmitted to a remote location for subsequent processing or storage. Statistical characteristics of the data are utilized to convert the data into a form that requires a reduced number of bits in accordance with the statistical characteristics. The data may be further compressed by transforming the data, as with a discrete cosine transform, and by modifying the transformed data in accordance with a quantization conversion table that is selected using a data type associated with the data. Additionally, a degree of redundancy may be removed from the processed data with an encoder. Subsequent processing of the compressed data may decompress the compressed data in order to approximate the original data by reversing the process for compressing the data with corresponding inverse operations.

Abstract: A SAR image auto-focus method uses statistics extracted from the image data to develop a phase pure hyperbolic correction function. The method processes an uncorrected azimuth line vector selected from an unfocused array into a corrected azimuth line vector. The method includes forming a bright spot list based on the selected uncorrected azimuth line vector where the bright spot list has at least one bright spot entry. Then, the uncorrected azimuth line vector is unpacked into an uncorrected segment set that has a first uncorrected segment corresponding to a first bright spot entry in the bright spot list. Then, the first uncorrected segment is processed into a first corrected segment based on an average phase slope corresponding to the first bright spot entry, the first corrected segment is packed into the corrected azimuth line vector, and the process repeated for all bright spots.

Abstract: An interferometric synthetic aperture radar (IFSAR) elevation measurement processor computes an elevation array by processing a first image array to generate an elevation corrected first image array, processing a second image array to generate an elevation corrected second image array, generating a phase interferogram from the elevation corrected first and second image arrays, and processing the phase interferogram to generate the computed elevation array. The layover correction is based on either (1) a predetermined elevation array, (2) an elevation array computed by radargrammetry, (3) an initial computed elevation array developed in an initial iteration by initial interferometry of uncorrected images followed by the layover correction in a subsequent iteration based on the initial computed elevation array, or (4) a combination of the above. The layover correction process removes range and Doppler distortion inherent in pixel data due to elevations variations in the imaged terrain.

Abstract: An interferogram is an array of phases, often generated from the inverse tangent of a ratio of an imaginary component divided by a real component. The array is said to be a wrapped phase array when the phase angle is modulo between zero and 2.pi.. A method of processing a wrapped phase array into an unwrapped phase array includes computing a first array from the wrapped phase array, each element of the first array being based on a discrete Poisson difference equation, processing the first array through a two dimensional FFT to form a second array, scaling the second array by a scaling function to form a third array, and processing the third array through an inverse two dimensional FFT to form the unwrapped phase array.