4148 results about "Covariance matrix" patented technology

In a MIMO system the signals transmitted from the various antennas are processed so as to improve the ability of the receiver to extract them from the received signal even in the face of some correlation. More specifically the number of bit streams that is transmitted simultaneously is adjusted, e.g., reduced, depending on the level of correlation, while multiple versions of each bit stream, variously weighted, are transmitted simultaneously. The variously weighted versions are combined to produced one combined weighted signal. The receiver processes the received signals in the same manner as it would have had all the signals reaching the receive antennas been uncorrelated. The weight vectors may be determined by the forward channel transmitter using the channel properties of the forward link which are made known to the transmitter of the forward link by being transmitted from the receiver of the forward link by the transmitter of the reverse link or the weight vectors may be determined by the forward channel transmitter using the channel properties of the forward link and the determined weight vectors are made known to the transmitter of the forward link by being transmitted from the receiver of the forward link by the transmitter of the reverse link. The channel properties used to determine the weight vectors may include the channel response from the transmitter to the receiver and the covariance matrix of noise and interference measured at the receiver.

A method comprises processing M subband communication signals and N target-cancelled signals in each subband with a set of beamformer coefficients to obtain an inverse target-cancelled covariance matrix of order N in each band; using a target absence signal to obtain an initial estimate of the noise power in a beamformer output signal averaged over recent frames with target absence in each subband; multiplying the initial noise estimate with a noise correction factor to obtain a refined estimate of the power of the beamformer output noise signal component in each subband; processing the refined estimate with the magnitude of the beamformer output to obtain a postfilter gain value in each subband; processing the beamformer output signal with the postfilter gain value to obtain a postfilter output signal in each subband; and processing the postfilter output subband signals to obtain an enhanced beamformed output signal.

A radio geolocation system is described in which a plurality of moving platforms such as aircraft concurrently receive a signal from a remote transmitter and the geolocation of the transmitter is determined. At each platform every thirty seconds a plurality of samples of the received signal are taken over a one second period. The samples are digitized and a time and GPS location stamp are added to each sample. The digitized samples with time and location stamps from all platforms are transmitted to a central location and stored in covariance matrices, one matrix per one second sample period. The signal samples in each matrix are processed utilizing a unique algorithm to generate a data set which defines a correlation surface. The data from a plurality of data sets are summed together on a point by point basis and normalized to yield a summation data set which defines a summation correlation surface. The summation correlation surface has a well defined peak that defines the geolocation of the remote transmitter.

A beam and power allocation method for a MIMO system transmitting multiple data streams from a transmitter having a plurality of transmit antennas to a receiver having at least two receive antennas, the transmit antennas being grouped based on feedback information from the receiver, includes obtaining covariance matrices for respective transmit antenna group, and allocating beam and power to the transmit antenna groups according to the covariance matrices of the respective antenna groups. The power allocation method can be adapted to various partial beamforming techniques by generalizing the optimization problem as a function of transmit covariance matrices.

A directional antenna system is disclosed in which a plurality of RF nodes are provided for cooperatively forming a directional antenna array for transmitting and receiving wireless signals between a wireless client at a predetermined position in space. One or more network interface assemblies are provided for exchanging signals between the plurality of RF nodes and a network. Preferably, the plurality of RF nodes are distributed in space with respect to each other and the network interface assembly. The network interface includes a beamformer for applying a plurality of antenna weighting factors to the respective RF nodes, for introducing phase differences in the respective transmitted and received wireless signals that produce a directional steering vector for the wireless signals. In one embodiment of the invention, a processing arrangement is provided for deriving an array manifold, which includes a respective plurality of antenna weighting factors corresponding respectively to distances between each of the plurality of RF nodes, for producing the directional steering vector for the wireless signals. In another embodiment of the invention, a subspace beamforming arrangement is provided for building a covariance matrix from sampled values of a wireless client signal at each RF node, and deriving dominant eigenvectors corresponding to each RF node. The dominant eigenvectors are used as the respective antenna weighting factors for producing the directional steering vectors for the wireless signals.

A system and method using a multi-element digital beamformer for detection and mitigation of spoofer and repeater threats to GPS that would not be addressed by baseline signal-to-noise (SNR) maximization algorithms is disclosed. GPS correlators and processing are applied to multiple beam outputs to detect and locate spoofer and repeater threats. In the beamformer processing, detected threats can be spatially nulled, even in the presence of traditional high power jamming, by modifying the normal sample covariance matrix to introduce synthetic nulls. A digital complex weighting system multiples each input channel by a complex (gain/phase) weight and adds the weighted channels together to form beams that the GPS receiver can use to reacquire the satellites in use without knowledge of platform attitude or the antenna manifold.

A system for efficiently filtering interfering signals in a front end of a GPS receiver is disclosed. Such interfering signals can emanate from friendly, as well as unfriendly, sources. One embodiment includes a GPS receiver with a space-time adaptive processing (STAP) filter. At least a portion of the interfering signals are removed by applying weights to the inputs. One embodiment adaptively calculates and applies the weights by Fourier Transform convolution and Fourier Transform correlation. The Fourier Transform can be computed via a Fast Fourier Transform (FFT). This approach advantageously reduces computational complexity to practical levels. Another embodiment utilizes redundancy in the covariance matrix to further reduce computational complexity. In another embodiment, an improved FFT and an improved Inverse FFT further reduce computational complexity and improve speed. Advantageously, embodiments can efficiently null a relatively large number of jammers at a relatively low cost and with relatively low operating power.

The present invention provides a method and system for receiving a plurality of transmission signals at a receiver, the transmission signals each traveling through a corresponding transmission channel. The receiver includes a plurality of receiver channels, a receiver channel corresponding to each transmission channel. Each receiver channel receives a corresponding transmission signal. The received transmission signals are detected to determine whether the received transmission signals are dominated by noise or interference. If the received transmission signals are dominated by noise, then a first set of weights are selected as a receiver weighting. If the received transmission signals are dominated by interference, then a second set of weights are selected as the receiver weighting. The received transmission signals are estimated based upon the receiver weighting. Detecting whether the received transmission signals are dominated by noise or interference includes determining a level of correlation between the received transmission signals. Detecting whether the received transmission signals are dominated by noise or interference can be determined during a time slot of nulled transmission signals. If the transmission signals are multiple carrier signals, then detecting whether the received transmission signals are dominated by noise or interference can be determined during a frequency and time slot of a nulled carrier of the transmission signals. The first set of weights can be based upon a first covariance matrix, wherein the first covariance matrix represents received noise and interference covariance. The second set of weights can be based upon the second covariance matrix, wherein the second covariance matrix represents interference covariance. The first set of weights and the second set of weights can also be used for transmission mode selection and receiver soft decoding.

A method for carrying out channel equalization in a radio receiver wherein an impulse response is estimated, noise power is determined by estimating a co-variance matrix of the noise contained in a received signal before prefiltering, and tap coefficients of prefilters and an equalizer are calculated. The method comprises determining the noise power after prefiltering by estimating a noise covariance matrix, after which input signals of the channel equalizer are weighted by weighting coefficients obtained from the noise covariance estimation.

A system and method of estimating the position of a mobile terminal (MT) operating in a radio telecommunications network. Expected Received Signal Strength (RSS) values are predicted by a computer-aided prediction tool, and/or are measured by a test MT from base station transceivers. The predicted and measured RSS values are then tagged to indicate whether each value was predicted or measured. The RSS values are then stored at a plurality of locations in a database. When RSS measurements are received from the MT being located, a covariance matrix is used to compute metrics for the locations in the database. If more than a threshold percentage of the locations were populated with measured values, a Maximum-Likelihood (ML) estimator is used to estimate the position of the MT. If fewer than the threshold percentage of locations were populated with measured values, a Minimum-Mean-Square-Error (MMSE) estimator is used to estimate the position.

A Dynamic Digital Pre-Distortion (DDPD) system is disclosed to rapidly correct power amplifier (PA) non-linearity and memory effects. To perform pre-distortion, a DDPD engine predistorts an input signal in order to cancel PA nonlinearities as the signal is amplified by the PA. The DDPD engine is implemented as a composite of one linear filter and N-1 high order term linear filters. The bank of linear filters have programmable complex coefficients. To compute the coefficients, samples from the transmit path and a feedback path are captured, and covariance matrices A and B are computed using optimized hardware. After the covariance matrices are computed, Gaussian elimination processing may be employed to compute the coefficients. Mathematical and hardware optimizations may be employed to simplify and reduce the number of multiplication operands and other operations, which can enable the DDPD system to fit within a single chip.

The invention provides a reconfigurable intelligent surface assisted multi-user MIMO uplink transmission method. According to the transmission method, a signal sent by a user side is reflected to a base station through an RIS, and the RIS can change the phase of the signal incident on the RIS. Aiming at a bottleneck problem of channel information acquisition of an RIS-assisted multi-user MIMO transmission system, only partial channel state information is utilized, including instantaneous channel state information from the RIS to a base station channel and statistical channel state informationfrom a user to the RIS channel; through an alternate optimization method, a deterministic equivalence principle, a block coordinate descent method, an MM method and the like, a sending covariance matrix and an RIS phase shift matrix of a user are jointly designed to maximize the global energy efficiency of the system or traverse the spectral efficiency; when the channel state information is changed, the user side dynamically implements transmission power distribution with maximum energy or spectral efficiency, and the RIS dynamically adjusts the phase shift matrix. According to the invention,the implementation complexity is low, and the performance of multi-user MIMO uplink transmission can be effectively improved.

The invention relates to mobile tracking of vehicle targets in the communication and transportation field. A self-adapting interactive multiple model mobile target tracking method comprises the following steps of establishing mixed initialized input. including a covariance matrix of a mixed initial condition and a mixed initial state. of each model; establishing constant velocity (CV) and constant acceleration (CA) motion models; updating: calculating covariance matrix and innovation of an error according to a Kalman filter formulation; constructing a likelihood function of a target motion module by utilizing the innovation of a Kalman filter result, and calculating a Markov state transition probability matrix; carrying out estimation output after being fused by utilizing the Markov state transition probability matrix as weight of switch among each motion model. According to the self-adapting interacting multiple model mobile target tracking method disclosed by the invention, the problem that the error is increased or the tracking is failed caused by non-matching of a filter model and a target motion model due to the motion of a target in the traditional interactive multiple model algorithm is solved; the self-adapting interacting multiple model mobile target tracking method has the advantages of low calculation complexity and good tracking effect, and can be applied to target tracking of motor vehicles in the communication and transportation field.

The invention discloses an image saliency detection method based on region description and priori knowledge. The method comprises the following steps that: (1) an image to be detected is subjected to pre-segmentation, superpixels are generated, and a pre-segmentation image is obtained; (2) a fusion feature covariance matrix of the superpixels is generated; (3) feature different region descriptors and space distribution region descriptors of each superpixel are calculated; (4) the initial saliency value of each pixel point of the image to be detected is calculated; (5) a priori saliency region and a background region of the image are obtained; (6) the saliency weight of each pixel point of the image to be detected is calculated; and (7) the final saliency value of each pixel point is calculated. The image saliency detection method has the advantages that the saliency region can be uniformly highlighted in an obtained final saliency map; the background noise interference is inhibited; a good saliency detection effect can be achieved in ordinary images, and the processing on the saliency detection of complicated images can also be realized; and the processing on subsequent image key region extraction and the like can also be favorably carried out.

Kernels (206) for use in learning machines, such as support vector machines, and methods are provided for selection and construction of such kernels are controlled by the nature of the data to be analyzed (203). In particular, data which may possess characteristics such as structure, for example DNA sequences, documents; graphs, signals, such as ECG signals and microarray expression profiles; spectra; images; spatio-temporal data; and relational data, and which may possess invariances or noise components that can interfere with the ability to accurately extract the desired information. Where structured datasets are analyzed, locational kernels are defined to provide measures of similarity among data points (210). The locational kernels are then combined to generate the decision function, or kernel. Where invariance transformations or noise is present, tangent vectors are defined to identify relationships between the invariance or noise and the data points (222). A covariance matrix is formed using the tangent vectors, then used in generation of the kernel.

The invention discloses a broadband signal DOA estimation method based on a co-prime array, and the method comprises the steps: S1, designing a co-prime array structure through an antenna; S2, carrying out the sampling and discrete Fourier transform of a broadband signal received by an antenna in the co-prime array, and obtaining a frequency domain signal output model; S3, calculating an autocorrelation matrix of the frequency domain signal output model, carrying out the vectorization of the frequency domain signal output model, and obtaining a new signal model; S4, carrying out the processing of the new signal model, and obtaining a spatial smooth covariance matrix of the broadband signal; Sa5, dividing a space domain grid, constructing a dictionary, carrying out the sparse representation of the spatial smooth covariance matrix through employing the dictionaries of a plurality of frequency points of the broadband signal, and forming a multi-measurement-vector sparse representation model of a plurality of dictionaries of the broadband signal; S6, achieving the arrival direction estimation of the broadband signal in a mode of solving a sparse inverse problem through the joint sparse constraint of the sparse representation coefficients of the plurality of dictionaries. The method can improve the estimation precision of the direction angle of the broadband signal under the condition of low signal to noise ratio, and reduces the direction finding error.

Apparatus and a method utilizing correlation interferometer direction finding for determining the azimuth and elevation to an aircraft at long range and flying at low altitudes above water with a transmitting radar while resolving multipath signals. The signals from the radar are received both directly and reflected from the surface of the water using horizontally polarized and vertically polarized antenna arrays, are digitized and are stored in separate covariant matrices. Eigenvalues for the eigenvectors of the matrices processed on signal samples recorded on horizontally polarized X arrays are compared to the eigenvalues for the eigenvectors of the covariance matrices processed on signal samples recorded on vertically polarized X arrays. Incident field polarization is associated with the antenna array measurements that yield the strongest eigenvalue. The eigenvector and eigenvalues for the strongest signal are selected and used for subsequent signal processing. An initial global search assuming mirror sea-state reflection conditions using the signal eigenvector having the strongest eigenvalue is performed to yield an approximate elevation α and azimuth β to the aircraft. The approximate values are then used as the starting point for a subsequent conjugate gradient search to determine accurate elevation α and azimuth β to the aircraft.

The invention discloses a method for estimating target arrival angle of a multiple input multiple output (MIMO) radar, which mainly solves the problem of large signal processing capacity in the target positioning process of MIMI radar. The method comprises the following steps of: 1) obtaining a virtual array of echo of each receiving antenna by a matched filter bank; 2) constructing a data conversion matrix and a dimension reduction array according to position of transmitting and receiving array; (3) reducing dimension of the virtual array data by the dimension reduction array to obtain an effective array after dimension reduction; 4) constructing two sub-arrays by rotational variance of effective array, and deriving covariance matrix of data; 5) decomposing eigenvalue of covariance matrix to obtain signal sub-spaces corresponding to two sub-arrays; 6) deriving rotational invariant relationship matrix by least square method to obtain arrival angle of target. The dimension reduction matrix form constructed by the method has versatility; the computation quantity is reduced by the dimension reduction of data and the ESPRIT (estimating signal parameter via rotational invariance techniques) algorithm; the computation speed of MIMO radar is increased; and the real-time signal processing of the MIMO radar is made easier.

The invention relates to an autonomous integrated navigation system which belongs to the technical field of navigation systems. The SINS (Strapdown Inertial Navigation System)/SAR (Synthetic Aperture Radar)/CNS (Celestial Navigation System) integrated navigation system takes SINS as a main navigation system and SAR and CNS as aided navigation systems and is established by the following steps: firstly, designing SINS/SAR and SINS/CNS navigation sub-filters, calculating to obtain two groups of local optimal estimation values and local optimal error covariance matrixes of the integrated navigation system state, then transmitting the two groups of local optimal estimation values into a main filter by a federal filter technology for fusion to obtain an overall optimal estimation value and an overall optimal error covariance matrix, and finally, performing real-time correction on the error according to the overall optimal estimation value so as to obtain an optimal estimation fusion algorithm of the SINS/SAR/CNS integrated navigation system. The autonomous integrated navigation system, disclosed by the invention, is less in calculation amount and high in reliability, is applicable to aircrafts in near space, aircrafts flying back and forth in the aerospace, aircrafts for carrying ballistic missiles, orbit spacecrafts and the like, and has wide application prospect.

The invention relates to a power battery management system of an electric automobile. In order to improve the estimating precision, the invention provides a method for estimating a charge state of a power battery of the electric automobile. The method comprises the following steps: acquiring the terminal voltage, the charging and discharging current and the battery surface temperature of the power battery; according to a corresponding relationship between the open-circuit voltage and the state of charge of the power battery, analyzing to obtain an open-circuit voltage model, and according to an input matrix, a parameter matrix and an output matrix of a dynamic voltage system of the power battery, establishing a dynamic voltage model of the dynamic voltage system; updating time and measurement of a state observer to obtain priori estimated values and posteriori estimated values of a system state as well as a covariance matrix of a system state estimating error at a time point k, and circulating the updating operation till the end of estimation to obtain the state of charge (SoC) of the power battery. By the method, the estimating precision of the SoC can be improved to be within 5%, and when a set value of the SoC of the power battery is deviated from a reference value of the SoC of the power battery, the SoC is rapidly converged to the reference value.

The invention provides an integrated navigation method and equipment based on multisource information fusion. The method comprises the following steps: obtaining multisource navigation information, namely obtaining navigation related information from one or more of a global satellite navigation system GNSS, an inertial navigation system INS, a multimode region difference augmentation system MLDAS, a pressure altimeter and timekeeping equipment, which are arranged on an aircraft; performing fusion treatment on multisource information by using a federal wave filter, wherein the federal wave filter comprises a main wave filter and a plurality of local wave filters connected with the main wave filter, and each kind of the multisource navigation information and a reference signal are jointly input to one local wave filter; triggering the local wave filters to respectively calculate local estimation values and error covariance matrixes; triggering the main wave filter to perform wave filtering on the reference signal, and performing optimal infusion on the wave filtering results of the reference signal according to output results of the local wave filters and the local wave filters, so as to obtain a global optimum estimation value. Therefore, the availability and the integrity of on-board navigation equipment are improved.

A method and apparatus is described for fusing a plurality of signals corresponding to estimates of the state of an object, system, or process. The method and apparatus is specialized or programmed for (1) receiving estimates, each of which can be expressed in the form of a state vector and an error covariance matrix, at least one estimate of which can be decomposed into a sum of an independent error covariance matrix and a potentially correlated error covariance matrix, and (2) transmitting a resulting signal corresponding to an estimate, which can be expressed in the form of a state vector and an error matrix, in order to evoke a physical response from a system receiving the signal. The method and apparatus provides advantages over the prior art by improving the accuracy of fused estimates while guaranteeing consistency.