Raytheon Company

The Boeing Company

United States of America as Represented by the Secretary of the Air Force

Leo H Hui

Kwang Myung Cho

Theagenis John Abatzoglou

Clifton Quan

Haig Francis Krikorian

Brendan H Robinson

Kenneth Ho

Daniel S Chew

John H Steele, Ii

John H Steele Ii

An example method executed by a controller onboard a spacecraft generates a mission plan in real-time that guides the spacecraft along a space autonomous mission to rendezvous with two or more orbiting target objects. The method includes establishing potential permutations for all possible unique maneuver sequences in which to visit the two or more orbiting target objects, and for each potential permutation, determining a collision-free maneuver plan for defining orbit trajectories to intercept each of the two or more orbiting target objects for each of the possible unique maneuver sequences. An optimal permutation is determined that meets viewing constraints of the two or more orbiting target objects, a viewing priority, and fuel constraints of the spacecraft. A mission visit plan is generated using the optimal permutation, and the spacecraft executes the plan to rendezvous with and inspect the two or more orbiting target objects.

Methods and systems for generating a mission plan that guides a spacecraft to orbiting target objects

A method that digitally distinguishes mainlobe detections from grating lobe and sidelobe detections without need for added antenna or receiver architecture. The method includes applying receive weights to return radar data for each radar receive element to steer each subarray of a array radar antenna to a direction other than the subarray transmit angle and includes applying a subarray weight to each subarray to generate the array radar antenna receive beam data having magnitude and phase components. The method includes applying predetermined scale factors to the subarray beam data magnitude for each subarray to generate scaled subarray beam data magnitudes. The method includes generating guard beam data for each subarray based on the scaled subarray beam data magnitudes. The method also includes determining if the return radar data corresponds to a mainlobe or a grating lobe or sidelobe based on the receive beam data and the guard beam data.

Grating lobe mitigation in presence of simultaneous receive beams

Systems and methods for determining a positional state of an airborne array antenna using distributed accelerometers are described. One such method includes receiving and formatting acceleration data from each of a plurality of accelerometers mounted at different locations along the array antenna, receiving position and orientation data from an inertial navigation service (INS) mounted on the array antenna, generating an INS estimated position for each accelerometer based on the position and orientation data from the INS, generating an accelerometer estimated position for each accelerometer based on the acceleration data, determining a position and orientation of each accelerometer based on the respective INS estimated position and the respective accelerometer estimated position, determining an estimated position of a center and an orientation of the array antenna based on the determined position and orientation of each accelerometer, and adjusting a direction of the array antenna based on the estimated position of the array antenna.

Systems and methods for determining a positional state of an airborne array antenna using distributed accelerometers

A method of target discrimination and identification, on a computer including a processing unit and a non-volatile storage device, from a radar signal having a plurality of radar return signals, is presented. The method includes: modeling, on the computer, the radar return signals by linear prediction to produce linear prediction equations; solving, on the computer, the linear prediction equations by the Burg algorithm to produce linear prediction coefficients for a linear prediction coefficient polynomial; computing, on the computer, roots of the linear prediction coefficient polynomial to produce scattering modes; computing, on the computer, a distance of each of the scattering modes to a unit circle; computing, on the computer, a complex envelope for each mode of the scattering modes; and selecting, on the computer, target scattering modes from among the scattering modes based on the distance of the mode to the unit circle and the complex envelope of the mode.

Enhanced target detection using dispersive vs non-dispersive scatterer signal processing

A moving radar generates a search mode synthetic aperture image of a patch having a principal scatterer. The boundaries of the patch are from Rto Rslant range and &#x3b8;to &#x3b8;azimuth angle. A computer motion compensates digital samples to obtain a motion compensated digital array. The motion compensated digital array is converted to a frequency array in the frequency domain K, KThe frequency array has a rectangular aperture extending &#x394;Kand &#x394;K. Available samples from the frequency array are computed using a Range Migration Algorithm including a Stolt interpolation. Usable samples are identified from the available samples using one or more criteria. Usable samples are removed from available samples to obtain incomplete samples. Features related to the patch having a principal scatterer are extracted from the usable samples. The features are used to extrapolate extrapolated samples from the usable samples. The extrapolated samples, the usable samples and the incomplete samples are combined to compute the image of the patch and principal scatterer. Incomplete samples are substituted where they overlap interpolated samples.

Restoration of signal to noise and spatial aperture in squint angles range migration algorithm for SAR

A moving radar () generates a synthetic aperture image from an incomplete sequence of periodic pulse returns. The incomplete sequence of periodic pulse returns has one or more missing pulses. The radar converts the incomplete sequence of pulse returns into a digital stream. A computer () processes the digital stream by computing an along track Fourier transform (), a range compression (), an azimuth deskew () and an image restoration and auto focus (). The image restoration and autofocus () utilizes a low order autofocus (), a gap interpolation using a Burg algorithm (), and a high order autofocus () for generating an interpolated sequence. The interpolated sequence contains a complete sequence of periodic pulse returns with uniform spacing for generating the synthetic aperture image. The image restoration and autofocus () computes a linear prediction coefficients estimate using the Burg Algorithm (). The linear prediction coefficients estimate () is used to compute a weighted forward-backward interpolation to generate the complete sequence of periodic pulse returns ().

Interrupt SAR implementation for range migration (RMA) processing

A radar acquires a formed SAR image of radar scatterers in an area around a central reference point (CRP). Target(s) are within the area illuminated by the radar. The area covers terrain having a plurality of elevations. The radar is on a moving platform, where the moving platform is moving along an actual path. The actual path is displaced from an ideal SAR image acquisition path. The radar has a computer that divides the digital returns descriptive of the formed SAR image into multiple blocks, such as a first strip and an adjacent strip. The first strip is conveniently chosen, likely to generally align with a part of the area, at a first elevation. An adjacent strip covers a second part of the area at a second elevation. The first strip is overlapping the adjacent strip over an overlap portion. The first and second elevation are extracted from a terrain elevation database (DTED). Horizontal displacement of returns (range deviation) is computed for each strip using the elevation information from the terrain elevation database. Taylor series coefficients are computed for the horizontal displacement due to terrain elevation using the ideal path, the actual path and central reference point. Actual flight path deviation is available at each pulse position while azimuth frequency is given in azimuth angle off mid angle point. Remapping between indices in two arrays is also computed. Phase error compensation and compensation in azimuth (spacial frequency) is computed using the Taylor series coefficients, a Fast Fourier Transform and an inverse Fast Fourier Transform for each strip. Phase error compensation is applied to the digital returns from each strip to obtain the SAR image. The SAR image is further improved by having the first strip corrected data and the second strip corrected data merged over the overlap portion to generate a relatively seamless SAR image.

Compensation of flight path deviation for spotlight SAR

A radar on a moving platform generates an initial synthetic aperture (SAR) image of a scene from a sequence of periodic pulse returns approximately motion compensated. The SAR image is formed from pixel intensities z(x,y) within a x,y extent of the initial synthetic aperture image. Targets are selected from the initial synthetic aperture image using a sliding window, computing a first entropy for the selected targets, and sorting the targets using the first entropy to obtain a target list having target elements, then concatenating the target elements to form a data matrix compatible in the azimuth dimension with a Fast Fourier Transform. A phase correction for autofocus is iteratively computed and applied to the initial synthetic aperture image using an inner loop, a mid loop and an outer loop. The phase correction is expressed using an orthogonal polynomial having a plurality n consecutive terms a, adenoting a quadratic term, and adenoting a last order term. The outer loop, using an L index, calculates an outer loop E(a) entropy for the quadratic term and an outer loop E(a) entropy for the last order term. Iterations within the outer loop continue until E(a)&#x2212;E(a) is less than an outer loop tolerance. Similarly, the mid loop, and inner loop continue until the computation of their respective entropies meet a pre-set tolerance. The inner loop entropy uses a Golden Section search for computing the inner loop entropy.

Autofocus method based on successive parameter adjustments for contrast optimization

A moving radar generates a search mode synthetic aperture image of a patch from periodic pulse returns reflected from the patch. The patch is imaged from radar returns derived from two or more overlapping arrays. A strong scatterer is located within each array, then the data from each array is motion compensated with respect to the motion of the radar and the strong scatterer. The motion compensated results for each array are autofocused to derive a phase error for each array. Using the phase error for each array, a connected phase error estimate is computed, added to the phase error of each array to minimize the differences between phases in the overlap between arrays insuring that there is no or minimal phase discontinuity in the overlap region between arrays. Avoiding phase discontinuity yields a clear SAR image of the combination of arrays rendering the patch.

Efficient autofocus method for swath SAR

SAR images are improved by a method for acquiring a synthetic aperture image from a sequence of periodic pulse returns where the sequence of periodic pulse returns is interspersed with interrupts, i.e. missing pulses. The interrupts mark the start and end of one or more segments, where the segments contain the periodic pulse returns form the SAR image. The method comprises the steps of: The computation for extrapolating the missing pulse returns is introduced after the Stolt interpolator in RMA processing. In computing the model order, eigenvalues are found and compared to a threshold. Roots of a linear prediction polynomial are computed, then stabilized to obtain stabilized roots. Linear prediction coefficients are reconstituted using the stabilized roots. Sub-bands are used to decrease computing time for the missing pulse returns.

Interrupt SAR image restoration using linear prediction and Range Migration Algorithm (RMA) processing

A stepped-frequency chirped waveform improves SAR groundmapping for the following reasons. Range resolution in SAR image is inversely proportional to the transmitted signal bandwidth in nominal SAR systems. Since there is a limit in the transmitted bandwidth that can be supported by the radar hardware, there is a limit in range resolution that can be achieved by processing SAR data in conventional manner. However, if the frequency band of the transmitted signal is skipped within a group of sub-pulses and received signal is properly combined, the composite signal has effectively increased bandwidth and hence improvement in range resolution can be achieved. The proposed new and practical approach can effectively extend the limit in range resolution beyond the level that is set by the radar hardware units when conventional method is used.

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Alhambra, CA, United States of America

Leo H Hui