71 results about "Orthogonal subspace" patented technology

This invention relates to a method and system for the radio location of CDMA and non-CDMA enabled transmitters within a reception zone. The invention exploits the superposition of antenna patterns that create complex and asymmetrical interference structures at very small scales. By randomly distributing a random antenna array of M elements across a two or three-dimensional surface, fine scale interference structures on the scale of ¼ the carrier wavelength are generated. Once the minimum number of antennas are placed, additional antennas will not improve the resolution. Such interference structures when sampled at ⅛ the carrier wavelength or greater yields unique spatial patterns with respect to a given antenna array geometry and transmitter location. The invention incorporates signature recognition (matching) and orthogonal sub-space projection estimators to derive location estimates of a radio transmitter.

This invention relates to a method and system for the radio location of CDMA and non-CDMA enabled transmitters within a reception zone. The invention exploits the superposition of antenna patterns that create complex and asymmetrical interference structures at very small scales. By randomly distributing a random antenna array of M elements across a two or three-dimensional surface, fine scale interference structures on the scale of ¼ the carrier wavelength are generated. Once the minimum number of antennas are placed, additional antennas will not improve the resolution. Such interference structures when sampled at 1 / 8 the carrier wavelength or greater yields unique spatial patterns with respect to a given antenna array geometry and transmitter location. The invention incorporates signature recognition (matching) and orthogonal sub-space projection estimators to derive location estimates of a radio transmitter.

The method discloses a method for detecting anomaly of a hyperspectral image, which can give consideration to advantages of an anomaly detecting method by global and local background modeling. The method comprises the following steps of: projecting a hyperspectral image to orthogonal subspaces of the background based on singular value decomposition so as to obtain a residual image including noise and anomaly; on the basis, introducing a space rank depth for local background modeling and dividing the residual image into two sample sets of noise background and potential anomaly; and finally, carrying out global background modeling by virtue of a multielement gaussian model, calculating the mahalanobis distance of various samples in the potential anomaly set, and comparing the distance with a threshold value to achieve anomaly detection, thus finally generating a binary mapping image capable of reflecting anomaly position coordinates and distribution regulation.

The invention provides a hyperspectral image anomaly detection method using multi-window feature analysis. The hyperspectral image anomaly detection method comprises the following steps: at first, determining the size of detected windows including an inner-layer window, a middle-layer window and an outer-layer window; next, calculating an OSP (Orthogonal Subspace Projection) operator in the outer-layer window, eliminating background interferences in the inner-layer window and the middle-layer window, and effectively removing white noise; then, carrying out background image element selection in the middle-layer window; and then, calculating a KRX (Kernel RX) operator in the inner-layer window, and carrying out anomaly detection on an image element to be detected; finally, outputting a detection result. According to the hyperspectral image anomaly detection method, a detection mode for three layers of windows is skillfully applied, and hyperspectral data is subjected to noise interference elimination at first and then is subjected to anomaly detection by using two layers of local background pixel windows. The interferences or the white noises emitted by uninterested signal sources in the inner-layer window and the middle-layer window are eliminated by using the OSP operator in the outer-layer window, so that the false alarm probability is reduced and better detection effect is obtained. A simulation experiment is carried out by using AVIRIS (Airborne Visible / Infrared Imaging Spectrometer) hyperspectral data, the detection performance of the hyperspectral image anomaly detection method provided by the invention is remarkably superior to the traditional algorithm, the false alarm possibility is reduced, and better detection effect is gained.

According to an asymmetric watermarking technology, which is particularly resistant to projection attack, an original image is analyzed to obtain its watermarking space. The watermarking space is then divided to obtain two orthogonal subspaces g and h. An embedding key G, which is a matrix and which columns form bases of subspace g, is selected and a matrix H, HTG=0 is calculated. Columns of matrix H form bases of subspace h. A detecting key D, which equals the sum D= GT=BHT, wherein B is a matrix, is calculated, and a watermark w is obtained and embedded into the original image φ0 to obtain a watermarked image φw=φ0+Gw, wherein Dφ0=m0 is not a 0 vector.

A method for compressive domain filtering and interference cancelation processes compressive measurements to eliminate or attenuate interference while preserving the information or geometry of the set of possible signals of interest. A signal processing apparatus assumes that the interfering signal lives in or near a known subspace that is partially or substantially orthogonal to the signal of interest, and then projects the compressive measurements into an orthogonal subspace and thus eliminate or attenuate the interference. This apparatus yields a modified set of measurements that can provide a stable embedding of the set of signals of interest, in which case it is guaranteed that the processed measurements retain sufficient information to enable the direct recovery of this signal of interest, or alternatively to enable the use of efficient compressive-domain algorithms for further processing. The method and apparatus operate directly on the compressive measurements to remove or attenuate unwanted signal components.

Systems and methods to monitor a signal from an apparatus are disclosed. A feature extracted from the signal is automatically defined. Signals are received over a period of time wherein the apparatus is in a normal operational mode. Features are classified in a learning mode and are applied to create a reference model that defines a within-normal operational mode. In a testing mode a signal generated by the apparatus is received, a feature is extracted and classified. Instantaneous data generated in operational mode by the apparatus is classified by the system as abnormal if it does not lie within boundaries of the reference model or contains information / structure in an orthogonal subspace. A learned reference model is augmented by a user or automatically. In one illustrative example the apparatus is a power generation equipment and the signal is an acoustic signal.

The invention discloses a hyperspectral image preprocessing method for unmixing of abnormal small targets so that a defect that abnormal small targets are easy to ignore according to the existing hyperspectral image preprocessing method serving the unmixing task can be solved. On the basis of characteristic of the small spatial scale of the target, a suspected target on a spatial dimension is determined by using a sliding window, a similarity measure weight is set based on a neighboring pixel position, and influences on determination of specificity of a to-be-measured pixel space by differentneighboring pixels in the window are treated in different ways; on the basis of the characteristic of specificity of a target spectrum relative to a background spectrum, suspected target determinationis carried at the feature dimension by using PCA transform; and then hyperspectral data are screened by combining a K-means method with an orthogonal subspace projection (OSP) method, so that the to-be-processed data volume is reduced effectively and the unmixing precision is improved. The great improvement space exists in engineering application. According to the invention, the follow-up end element extraction stage does not need to be modified; and the algorithm application is flexible.