Abstract: A load balancing method and a load balancing system are described in the present disclosure. In a load balancing process, services that can be provided by a service provision module are registered, after a service use module initiates a service request, a list of service provision modules that can provide a corresponding service is acquired according to the request, and then according to the list, a service provision module is selected from the list through a load balancing algorithm to perform the service requested by the service use module.

Abstract: A spotlight synthetic aperture radar (SAR) image is generated by directing randomly a beam of transmitted pulses at a set of two or more areas using a steerable array of antennas. Each area is illuminated by an approximately equal number of the transmitted pulses. Then, a reconstruction procedure is applied independently to received signals from each area due to reflecting the transmitted pulses to generate the image corresponding to the set of areas.

Abstract: A method reconstructs a scene behind a wall by transmitting a signal through the wall into the scene. Parameters of the wall are estimated from a reflected signal. A model of a permittivity of the wall is generated using the parameters, and then the scene is reconstructed as an image from the reflected signal using the model and sparse recovery.

Abstract: A system and method determines a noise free image of a scene located behind a wall. A transmit antenna emits a radar pulse from different locations in front of the wall, wherein the radar pulses propagate through the wall and are reflected by the scene as echoes. A set of stationary receive antennas acquire the echoes corresponding to each pulse transmitted from each different location. A radar imaging subsystem connected to the transmit antenna and the set of receive antennas determines a noisy image of the scene for each location of the transmit antenna. A total variation denoiser denoises each noisy image to produce a corresponding denoised image. A combiner combines incoherently the denoised images to produce the noise free image.

Abstract: A synthetic aperture radar image is generated by directing randomly a beam of transmitted pulses at an area using a steerable array of antennas, wherein the area is uniformly by the transmitted pulses while the array of antennas moves along a path. A sparse reconstruction procedure is applied to received signals from the area due to reflecting the transmitted pulses to generate the image corresponding to the area. The radar system can operate in either sliding spotlight mode, or scan mode. The area can be of an arbitrary shape, and a resolution of the image can be increased.

Abstract: A method generates a 3D synthetic aperture radar (SAR) image of an area by first acquiring multiple data sets from the area using one or more SAR systems, wherein each SAR system has one or more parallel baselines and multiple pulse repetition frequency (PRF), wherein the PRF for each baseline is different. The data sets are registered and aligned to produce aligned data sets. Then, a 3D compressive sensing reconstruction procedure is applied to the aligned data sets to generate the 3D image corresponding to the area.

Abstract: A method reconstructs a scene behind a wall by transmitting a signal through the wall into the scene. Parameters of the wall are estimated from a reflected signal. A model of a permittivity of the wall is generated using the parameters, and then the scene is reconstructed as an image from the reflected signal using the model and sparse recovery.

Abstract: A synthetic aperture radar image is generated by directing randomly a beam of transmitted pulses at an area using a steerable array of antennas, wherein the area is uniformly by the transmitted pulses while the array of antennas moves along a path. A sparse reconstruction procedure is applied to received signals from the area due to reflecting the transmitted pulses to generate the image corresponding to the area. The radar system can operate in either sliding spotlight mode, or scan mode. The area can be of an arbitrary shape, and a resolution of the image can be increased.

Abstract: A spotlight synthetic aperture radar (SAR) image is generated by directing randomly a beam of transmitted pulses at a set of two or more areas using a steerable array of antennas. Each area is illuminated by an approximately equal number of the transmitted pulses. Then, a reconstruction procedure is applied independently to received signals from each area due to reflecting the transmitted pulses to generate the image corresponding to the set of areas.

Abstract: A method Pan-sharpens a single panchromatic (Pan) image and a single multispectral (MS) image. A wavelet transform is applied to the Pan image and the MS image to obtain a wavelet transformed Pan image and a wavelet transformed MS image. Features, in the form of vectors, are extracted from the wavelet transformed Pan image and the wavelet transformed MS image. The features are separated into features without missing values and features with missing values. A dictionary is learned from features without missing values and used to predict the values for the features with the missing values. After the predicting, the features of the low frequency wavelet coefficients and the high frequency coefficients to form a fused wavelet coefficient map, and an inverse wavelet transform is applied to the fused wavelet coefficient map to obtain a fused MS image.

Abstract: A single panchromatic (Pan) image and a single multispectral (MS) image are Pan-sharpened by extracting features from the Pan image and the MS image. The features are decomposed into features without missing values and features with missing values. A dictionary is learned from the features without missing values. The values for the features with the missing values are learned using the dictionary. The MS image is merged with the Pan image including the predicted values into a merged image, and the merged image is then Pan sharpened.

Abstract: A synthetic aperture radar (SAR) system includes a non-uniform pulse generator, and an echo receiver. A SAR image is reconstructed from samples of received echoes, wherein transmitted pulses and reflected echoes overlap in time.

Abstract: A single panchromatic (Pan) image and a single multispectral (MS) image are Pan-sharpened by extracting features from the Pan image and the MS image. The features are decomposed into features without missing values and features with missing values. A dictionary is learned from the features without missing values. The values for the features with the missing values are learned using the dictionary. The MS image is merged with the Pan image including the predicted values into a merged image, and the merged image is then Pan sharpened.

Abstract: A method Pan-sharpens a single panchromatic (Pan) image and a single multispectral (MS) image. A wavelet transform is applied to the Pan image and the MS image to obtain a wavelet transformed Pan image and a wavelet transformed MS image. Features, in the form of vectors, are extracted from the wavelet transformed Pan image and the wavelet transformed MS image. The features are separated into features without missing values and features with missing values. A dictionary is learned from features without missing values and used to predict the values for the features with the missing values. After the predicting, the features of the low frequency wavelet coefficients and the high frequency coefficients to form a fused wavelet coefficient map, and an inverse wavelet transform is applied to the fused wavelet coefficient map to obtain a fused MS image.

Abstract: A synthetic aperture radar (SAR) system includes a non-uniform pulse generator, and an echo receiver. A SAR image is reconstructed from samples of received echoes, wherein transmitted pulses and reflected echoes overlap in time.