Sandia Corporation

National Technology & Engineering Solutions of Sandia, LLC

Douglas L Bickel

Armin W Doerry

Richard M Naething

Timothy P Bielek

Ana Martinez

Richard C Ormesher

Cameron H Musgrove

Jeff A Hollowell

Margaret S Murray

Volker Horndt

Brian P Mileshosky

David A Yocky

William H Hensley, Jr

David W Harmony

Various technologies for mitigating interference artifacts in multi-pass synthetic aperture radar (SAR) imagery are described herein. First and second phase histories corresponding to first and second SAR passes over a scene are processed in image and phase-history domains to correct for spatially-variant and constant phase offsets between the phase histories that can be caused by known and unknown variations in motion of a SAR platform between passes. Data samples from one phase history can then be replaced with data samples from the other phase history to remove artifacts and distortions caused by sources of interference in the scene.

Spectral replacement to mitigate interference for multi-pass synthetic aperture radar

The various technologies presented herein relate to identification and mitigation of spurious energies or signals (aka 'spurs') in radar imaging. Spurious energy in received radar data can be a consequence of non-ideal component and circuit behavior. Such behavior can result from I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), etc. The manifestation of the spurious energy in a radar image (e.g., a range-Doppler map) can be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images which have been processed using the same data but of different signal paths and modulations enables identification of undesired spurs, with subsequent cropping or apodization of the undesired spurs from a radar image. Spurs can be identified by comparison with a threshold energy. Removal of an undesired spur enables enhanced identification of true targets in a radar image.

Apodization of spurs in radar receivers using multi-channel processing

The various technologies presented herein relate to utilizing direction of arrival (DOA) data to determine various flight parameters for an aircraft A plurality of radar images (e.g., SAR images) can be analyzed to identify a plurality of pixels in the radar images relating to one or more ground targets. In an embodiment, the plurality of pixels can be selected based upon the pixels exceeding a SNR threshold. The DOA data in conjunction with a measurable Doppler frequency for each pixel can be obtained. Multi-aperture technology enables derivation of an independent measure of DOA to each pixel based on interferometric analysis. This independent measure of DOA enables decoupling of the aircraft velocity from the DOA in a range-Doppler map, thereby enabling determination of a radar velocity. The determined aircraft velocity can be utilized to update an onboard INS, and to keep it aligned, without the need for additional velocity-measuring instrumentation.

Radar velocity determination using direction of arrival measurements

A synthetic aperture radar (SAR) image is produced by using all phase histories of a set of phase histories to produce a first pixel array having a first azimuth resolution, and using less than all phase histories of the set to produce a second pixel array having a second azimuth resolution that is coarser than the first azimuth resolution. The first and second pixel arrays are combined to produce a third pixel array defining a desired SAR image that shows distinct shadows of moving objects while preserving detail in stationary background clutter.

Synthetic aperture radar images with composite azimuth resolution

Radar data associated with radar illumination of a movable target is processed to monitor motion of the target. A plurality of filter operations are performed in parallel on the radar data so that each filter operation produces target image information. The filter operations are defined to have respectively corresponding velocity ranges that differ from one another. The target image information produced by one of the filter operations represents the target more accurately than the target image information produced by the remainder of the filter operations when a current velocity of the target is within the velocity range associated with the one filter operation. In response to the current velocity of the target being within the velocity range associated with the one filter operation, motion of the target is tracked based on the target image information produced by the one filter operation.

Tracking moving radar targets with parallel, velocity-tuned filters

The location of a land-based radio frequency (RF) emitter is determined from an airborne platform. RF signaling is received from the RF emitter via first and second antennas. In response to the received RF signaling, signal samples for both antennas are produced and processed to determine the location of the RF emitter.

Using antennas separated in flight direction to avoid effect of emitter clock drift in geolocation

Radar systems use time delay measurements between a transmitted signal and its echo to calculate range to a target. Ranges that change with time cause a Doppler offset in phase and frequency of the echo. Consequently, the closing velocity between target and radar can be measured by measuring the Doppler offset of the echo. The closing velocity is also known as radial velocity, or line-of-sight velocity. Doppler frequency is measured in a pulse-Doppler radar as a linear phase shift over a set of radar pulses during some Coherent Processing Interval (CPI). An Interferometric Moving Target Indicator (MTI) radar can be used to measure the tangential velocity component of a moving target. Multiple baselines, along with the conventional radial velocity measurement, allow estimating the true 3-D velocity of a target.

Tangential velocity measurement using interferometric MTI radar

A multi-antenna, multi-pass IFSAR mode utilizing data driven alignment of multiple independent passes can combine the scaling accuracy of a two-antenna, one-pass IFSAR mode with the height-noise performance of a one-antenna, two-pass IFSAR mode. A two-antenna, two-pass IFSAR mode can accurately estimate the larger antenna baseline from the data itself and reduce height-noise, allowing for more accurate information about target ground position locations and heights. The two-antenna, two-pass IFSAR mode can use coarser IFSAR data to estimate the larger antenna baseline. Multi-pass IFSAR can be extended to more than two (2) passes, thereby allowing true three-dimensional radar imaging from stand-off aircraft and satellite platforms.

Two antenna, two pass interferometric synthetic aperture radar

IFSAR images of a target scene are generated by compensating for variations in vertical separation between collection surfaces defined for each IFSAR antenna by adjusting the baseline projection during image generation. In addition, height information from all antennas is processed before processing range and azimuth information in a normal fashion to create the IFSAR image.

Error correction for IFSAR

Interferometric synthetic aperture radar (IFSAR) is a promising technology for a wide variety of military and civilian elevation modeling requirements. IFSAR extends traditional two dimensional SAR processing to three dimensions by utilizing the phase difference between two SAR images taken from different elevation positions to determine an angle of arrival for each pixel in the scene. This angle, together with the two-dimensional location information in the traditional SAR image, can be transformed into geographic coordinates if the position and motion parameters of the antennas are known accurately.

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Albuquerque, NM, United States of America

Douglas L Bickel