Hughes Aircraft Company

Yoji G Niho

Ralph E Hudson

Tammy L Flanders

Eric W Day

A method and autofocus processor that is adapted to automatically correct focus phase errors associated with synthetic array radar signals. The method comprises processing the synthetic array radar signals to produce a SAR image; identifying and locating potential targets contained in the SAR image; storing the range bin and azimuth location of the target in a target list; bandpass filtering the SAR signals associated with the target scatterer to remove the interference therefrom; forming the pulse pair product of the phase history samples from each reference target to produce a differential phase function; integrating the differential phase function over all reference targets to provide the averaged differential phase history associated therewith; interpolating the averaged differential phase function to restore the original time scale and number of samples; and computing the focus error from interpolated differential phase history. The focus error is estimated as a weighted average of the phase history of the detected scatterers. The autofocus processor automatically finds targets and combines data from multiple scatterers effectively and efficiently. The autofocus processor extends the range and resolution limits of SAR systems, and enables the effective use of a SAR sensor with less expensive motion compensation function. The autofocus processor also decouples the SAR sensor (including motion sensors) from its SAR processor, so that the autofocus processor produces better images, no matter what sensor is employed.

Multiple discrete autofocus

The present invention is a computational method, defined by a computational algorithm, that automatically corrects synthetic array radar (SAR) focus errors more accurately than conventional procedures. The novel feature is that the present method estimates residual phase errors by forming fourth-order subarray products in lieu of conventional second-order subarray products. As a result, a pull-in range for residual phase errors is vastly improved. The present invention advances the state of the art by creating a SAR autofocus method that has an unlimited pull-in range for both a quadratic and a cubic phase errors. The invention thus extends the operational range and resolution of SAR systems, and enables the effective use of the SAR sensor with a limited (less expensive) motion compensation subsystem. The present invention provides for a phase difference autofocus method that estimates the residual quadratic and cubic phase error that often requires only one autofocus iteration.

Fourth-order-product phase difference autofocus

A phase difference autofocus method that only requires one FFT for estimating a phase error in the entire synthetic array radar data. The phase difference autofocus method of the present invention automatically and efficiently estimates phase errors from radar signals, allowing a well focused SAR image to be produced. The present method comprises the following steps. First, each range bin is divided into two subarrays. Next, the two subarrays are complex-conjugate multiplied together to produce a cross spectrum of the two submaps produced by the subarrays. Then, the phases of each cross spectrum are aligned with an accumulated sum of the cross spectrums from previous processed range bins. The phase aligned cross spectrum is then added to the accumulated cross spectrum sum. All range bins are processed to get a final cross spectrum sum. Next, a single FFT is performed on the final cross spectrum sum to produce the cross correlation function. Then, the cross correlation function is magnitude-detected. Since the location of the peak of the cross correlation function is proportional to the phase error, a phase error estimate is obtained. Finally, the phase error correction signal is produced for the entire synthetic array radar data. Since only one FFT is performed during autofocus processing, the method is relatively fast.

Fast phase difference autofocus

The invention provides improved focus by phase corrections for Synthetic Aperture Radar images by operation on the range bin containing a selected isolated target. A phase correction signal is generated by first obtaining a non-interfering radar return from the selected target through band pass filtering operation and then extracting a non-linear residual phase from the band pass filtered data with an arc-tangent generator. The residual phase derived by the arc-tangent generator is then applied to the range compressed SAR data as a phase correction signal.

Discrete autofocus for ultra-high resolution synthetic aperture radar

The present invention discloses an autofocusing method and apparatus for Synthetic Aperture Radar which employs operation on two or three subarrays of the SAR compressed data to estimate quadratic and cubic phase errors in the data. Focusing of the SAR array may then be accomplished by removing the estimated phase error from the data to sharpen the image. Phase error is estimated by FFT filtering product arrays formed by multiplying the complex conjugate of one subarray by another of the subarrays to form a correlation function. The correlation functions are integrated. A peak detection of the integrated correlation functions yields a peak location in the filter which is proportional to the phase error which may then be calculated.

Phase difference auto focusing for synthetic aperture radar imaging

A technique is disclosed for encoding SAR image data to achieve data compression. In the image encoding stage, the SAR image is transformed into a list of high reflectivity radar discretes and a small array of frequency filters. In the target list, the location data and intensity levels above the local average background clutter are tabulated for a predetermined number of the highest intensity radar discretes. The array of frequency filters is divided into three zones; the inner, middle, and higher frequency zones relative to the d.c. filter. Only the inner and middle zones of filters are retained and the outer filters are discarded, thus acheiving the desired data reduction. The inner zone filters are quantized to a higher level of precision than the middle zone of filters. The saturation levels of the filters are determined adaptively. In the decoding stage, the original SAR image is reconstructed from the radar discrete list and the small array of frequency filters.

Growing community of inventors

Rancho Palos Verdes, CA, United States of America

Yoji G Niho