Abstract: Agent/client pairs in at least one priority tier are determined. A matrix value is determined for each agent/client pair based on the client rank of the agent/client pair. An engagement capability parameter is determined for each agent/client pair. The matrix value for each disallowed agent/ranked client value is set to a zero value. All possible engagement options are evaluated. Candidate pair paths are determined by determining pair paths having a highest initial path value. The initial path value of each candidate pair path is decreased based on agent/client pairs in the candidate pair path that are urgent agent/client pairs or risky agent/client pairs to derive a final path value for each candidate pair path. A best path is determined based on the final path value for each candidate pair path. At least one engagement decision is derived based on the best path and transmitted towards agents in the best path.

Abstract: 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.

Abstract: Systems and methods for determining a positional state of an airborne array antenna using distributed accelerometers are described.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems and methods for determining a positional state of an airborne array antenna using distributed accelerometers are described.

Abstract: A moving radar generates a search mode synthetic aperture image of a patch having a principal scatterer. The boundaries of the patch are from R0 to R1 slant range and ?0 to ?1 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 Kx, Ky The frequency array has a rectangular aperture extending ?Kx and ?Ky. 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.

Abstract: A moving radar (405) 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 (403) processes the digital stream by computing an along track Fourier transform (402), a range compression (408), an azimuth deskew (410) and an image restoration and auto focus (412). The image restoration and autofocus (412) utilizes a low order autofocus (501), a gap interpolation using a Burg algorithm (503), and a high order autofocus (505) 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 (412) computes a linear prediction coefficients estimate using the Burg Algorithm (606).

Abstract: 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).

Abstract: 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.

Abstract: 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 zn(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 an, a2 denoting a quadratic term, and aN denoting a last order term.

Abstract: 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: converting said pulse returns into a digital stream; performing an azimuth deskew on said digital stream to obtain a deskewed digital stream; forming a forward-backward data matrix from the deskewed digital stream for one or more segments; forming an average segment covariance from the forward-backward data matrix; computing a model order for the average segment covariance; computing one or more linear prediction coefficients using data contained in the forward backward data matrix, and model order; using the linear prediction coefficients to compute missing pulse returns belonging within the interrupts.

Abstract: 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.

Abstract: A radar system has improved range resolution from linear frequency modulated (LFM) first sub-pulse and second sub-pulse, both having linear frequency modulation about different center frequencies. The first transmitted sub-pulse and the second transmitted sub-pulse have chirp slope &ggr;. Sample shifting and phase adjusting is performed for the first radar returns with respect to second radar returns to form a line of frequency modulated chirp slope &ggr; with respect to time, the line connecting the center frequencies of the center frequencies. The first sub-pulse and second-sub pulse can have equal time duration, where the first and second center frequency are equidistant from a reference frequency. The returns are reflected by a target located at a location near a reference point s.

Abstract: A range cell formation process that are used to enhance the quality of an image following a perspective transformation from range-azimuth coordinates (B-scan) into elevation-azimuth coordinates (C-scan). The present range cell formation process eliminate situations where there are missing data points at the far range, and large areas that have the same data point at the near range. The range cell formation process evaluates the data content in range cells on a case by case basis using a prioritized system to determine what is to be displayed so that a high level of image contrast is maintained. In the far range, range cell data that are in between range points defined by every two adjacent elevation points are processed and a priority system is used to determine the best intensity value to use for the elevation points. The priority system is such that bright objects have the highest priority, followed by dark objects, and then followed by an average background level.

Abstract: A high speed and high precision coordinate transformation process for transforming image data in range-azimuth coordinates to horizontal-vertical display coordinates. The process is comprised of the following steps. Recursion initialization parameters and values for a perspective transformation are computed. Then, range and azimuth values using predetermined recursion equations are computed. A critical range factor using predetermined recursion equations and inverse operation is computed. Range and azimuth results are computed. Display address values are computed. Data is retrieved and the data is stored in display locations. A decision is then made whether the last display address has been stored. Additional display address values are computed until all addresses have been computed, and the process is ended once all addresses have been computed.

Abstract: A monopulse thresholding processor and method for improving resolution by using the difference channel data to eliminate "excess" sum channel returns. The processor may be used with a radar system that comprises an antenna, a transminer, a receiver for processing transmitted radar signals to produce radar returns therefrom, a log compressor for converting radar returns to log values, and a display for displaying the radar returns. The signal processor comprises a left sum and right sum generator coupled to the receiver for computing a left sum and a right sum from radar returns generated by the receiver. A pseudo-difference generator is coupled to the left sum and fight sum generator for generating pseudo-difference channel data. A beam sharpener is coupled to the left sum and right sum generator and to the pseudo-difference generator for beam sharpening the radar returns.