52 results about "Capon" patented technology

The invention discloses a robust wave beam forming method based on covariance matrix reconstruction and guide vector estimation. The method comprises the steps: firstly carrying out the eigenvalue decomposition of a covariance matrix of received data of an antenna, obtaining a noise subspace, estimating an arrival angle of an interference signal through a multi-signal classification method, calculating a guide vector, carrying out the correction through a robust Capon wave beam forming algorithm, solving the power of the interference signal according to the orthogonality of the guide vector, and constructing an interference and noise covariance matrix; constructing a constraint condition of an expected signal guide vector through finding the space orthogonal to the expected signal guide vector, and solving a precise expected signal guide vector according to the maximum output power. The method is robust for a guide vector error and an interference and noise covariance matrix error, which are caused by an array position error, a non-interconnection local scattering and total amplitude and phase errors. Compared with the prior art, the method is higher in output signal to interference and noise ratio, and is higher in output performances.

A method for resisting primary user impersonation attacks in cognitive radio belongs to the technical field of radio communication, particularly relates to sensing and processing of the signals in the cognitive radio system and identification of a signal source. The method comprises the following steps: reducing noise of a composite signal which is received during a spectrum sensing process, estimating number of the signal sources in the composite signal, and reconstructing various signals by a Capon beamformer; separating the signals of different radios, focusing the signals of different radios to separate out a transient signal and a modulation signal, analyzing the transient signal by wavelet transformation; extracting characteristic parameters and realizing identification of the signal source. The method for resisting the primary user impersonation attacks helps realize effective identification of the signal source and effectively resist the primary user impersonation attacks; and the method has a wide application scope, does not change a working mode of the existing primary user network, and satisfies operation requirements of FCC for a cognitive network.

The invention belongs to the technical field of MIMO radars, and provides a high resolution DOA estimation method and system. The method includes the following steps that all receiving antennas receive transmitting signals reflected by target sources; a receiving signal of each receiving antenna is scanned through the transmitting signals, so that the corresponding relay of each transmitting signal is obtained; the transmitting signals are adjusted according to the obtained delay, the conjugate of each adjusted transmitting signal is multiplied with the receiving signal of each antenna, and accordingly the phase positions, corresponding to all peak points, in the receiving signal of each receiving antenna are obtained; virtual expansion signals are established according to the obtained phase positions and adjusted transmitting waveform signals; novel receiving signals are formed by the virtual expansion signals and the receiving signals, the covariance and the Capon wave beams of the novel receiving signals are calculated to form coefficients, and thus DOA estimation is completed. According to the high resolution DOA estimation method and system, under the condition that antennas are not additionally arranged, estimated accuracy can be improved, and the number of target sources which can be estimated can be increased.

The invention belongs to the field of array signal processing and mainly relates to robustness of a standard Capon self-adaptive beam forming algorithm based on covariance matrix reconstruction to interference signal steering vector errors. The beam forming algorithm based on subspace interference-plus-noise covariance matrix reconstruction comprises the following steps: at first, utilizing matrix received data to estimate the steering vector a(theta d), d=2,3,...,D and the power sigma<2> d(theta d) of all D-1 interference signals and meanwhile estimate the noise power sigma<2>, wherein d=2,3,...,D; then reconstructing an interference-plus-noise covariance matrix R' according to the definition R of the interference-plus-noise covariance matrix; finally, constructing a signal covariance matrix in a relatively small angle range 1; taking the dominant eigenvector of the signal covariance matrix as a desired signal steering vector to estimate a(theta 1); together with the reconstructed R', obtaining a novel beam forming weighing vector W, wherein the formulas of R, R' and W are shown in the description. The beam forming method provided by the invention overcomes the defects of the conventional beam forming algorithm, thereby having good robustness to interference signal steering vector errors.

The invention discloses a sparse construction and reconstruction method of array space signals. Due to the fact that the angle of received incident signals changes constantly under the high dynamic condition, enough sampling signals can not be acquired to conduct traditional beam forming. According to the method, a gain test of the array space signals is conducted through the Capon beam forming method based on feature space decomposition, and establishment of a small-snapshot-number sparseness model and OPM reconstruction of the small-snapshot-number sparseness model are conducted based on the compressed sensing theory. The result shows that the method has the advantage of processing undersampled data and achieves estimation on the angle of arrival of the array signals. The method further shows that in the space signal processing field, sparsity makes extraction of related information faster and more effective, so that the signal acquisition cost and the signal processing cost are lowered. By means of the method, expected waveform gain can be obtained in the expected direction of arrival. Compared with a direct sampling method, the method can solve the small snapshot number problem occurring under the high dynamic condition and improve the robustness of a system.

The invention discloses a GPS (global positioning system) multi-path mitigation method based on a robust beam forming algorithm, which comprises the following steps: step I, modeling a GPS multipath channel by adopting a uniform linear array; step II, performing decorrelation on received signals by adopting the forward-backward spatial-smoothing technology, so as to obtain a new data covariance matrix and the optimal weight of a Capon beam former; step III, on the basis of the step II, establishing a cost function of the worst-case performance optimization robust beam forming algorithm, so as to solve the optimal weight under steering vector mismatch; step IV, on the basis of the step III, exerting uncertainty constraint on other array response errors, so as to obtain an improved model for the worst-case performance optimization robust beam forming algorithm; and step V, according to the model determined in the step IV, calculating to obtain the optimal weight vector of the Capon beam former, and determining the loading capacity by utilizing the Newton iteration method.

A robust adaptive beam formation method disclosed by the present invention comprises a step 1 of utilizing a Capon space power spectrum to estimate the average noise power in an angle area only containing the stationary noise, and obtaining a corresponding noise covariance matrix; a step 2 of adopting the Capon space power spectrum to collect all interference information located in an interferencesignal angle area, rejecting a noise component, and reconstructing an interference covariance matrix; then reconstructing an interference and noise covariance matrix according to the noise covariancematrix and the interference covariance matrix; a step 3 of correcting a steering vector of a desired signal of a beam former according to the reconstructed interference and noise covariance matrix, calculating an optimal weight vector, and forming a robust adaptive beam. The method can obtain the more accurate interference and noise covariance matrix and the steering vector of the desired signal,so that the robustness of the adaptive beam formation method on various array error conditions is improved further.

The invention is applicable to the technical field of vehicle-mounted radars and provides a method for detecting people in a vehicle, a radar and a vehicle. The method comprises the following steps of: acquiring a plurality of paths of target echo signals when people are in the vehicle, and preprocessing each path of target echo signals to obtain a plurality of paths of digital target signals; calculating a CAPON spectrum of the plurality paths of digital target signals to obtain target two-dimensional thermodynamic diagram information, and establishing an in-vehicle people identification model according to the target two-dimensional thermodynamic diagram information; acquiring multiple paths of echo signals to be detected in the vehicle, repeating the steps of preprocessing and calculating the CAPON spectrum to obtain the two-dimensional thermodynamic diagram information to be detected, and determining whether people are in the vehicle or not according to the in-vehicle people identification model and the two-dimensional thermodynamic diagram information to be detected. The embodiment of the invention is not influenced by the environment, can accurately detect whether a resident person exists in the vehicle, and ensures the personal safety of resident children or people who are inconvenient to move in the vehicle.

A method for enhanced Capon beamforming includes the steps of providing a sensor array including a plurality of sensor elements where an array steering vector corresponding to a signal of interest (SOI) is unknown. A covariance matrix fitting relation is bounded for the unknown array steering vector by constraining the array steering vector using a constant norm and a spherical uncertainty set. The matrix fitting relation is then solved to provide an estimate of said array steering vector.

The invention discloses a method for improving the quality of a three-dimensional interferometric inverse synthetic aperture radar (ISAR) image. The method comprises the following steps: pre-processing echo data; carrying out azimuth aperture extrapolation on the echo data by using a spectrum estimation technology to obtain an interference pair of a super-resolution two-dimensional interferometric synthetic aperture radar image; registering the super-resolution two-dimensional interferometric synthetic aperture radar image and carrying out interference processing to obtain the three-dimensional interferometric inverse synthetic aperture radar image under different spectrum estimation technologies. The step of pre-processing the data comprises movement compensation processing on the echo data of each antenna platform, compensation of a wave path difference between antennas and elimination of migration though resolution cell by Keystone conversion; a Capon spectrum estimation technology and a Burg spectrum estimation technology are used for carrying out the azimuth aperture extrapolation to obtain the super-resolution two-dimensional ISAR image pairs under different methods; by adopting the method, a high-quality actual measurement target three-dimensional view can be obtained and the method has very important meanings on ISAR target identification and posture determination.

The invention provides a shallow sea target direction-of-arrival estimation method based on active time reversal and relates to the fields of shallow water acoustic channel, active time reversal and array signal processing. The method is characterized in that the target receives a signal and carries out reflection; each array element of a uniform linear array receives the reflected signal, and thesignal received by the array element is popularized to each array element; the received signal of each array element is subjected to filtering, and then, is subjected to time reversal processing; theuniform linear array receives the signal for the second time; after time reversal, a sample covariance matrix of array output signals is obtained; a spatial spectrum function is obtained through a Capon algorithm; and spectrum peak search is carried out on the spatial spectrum function to estimate the direction of arrival of the target. The method carries out target DOA estimation based on the active time reversal, so that the method is higher in estimation precision, better in sidelobe suppression capability and can be better applied to DOA estimation under low signal-to-noise ratio and multipath conditions.

The present invention discloses a coherent signal source MIMO radar angle estimation method in non-stationary noise. The method concretely comprises the steps of: 1, performing system initialization;2, obtaining signal data being subjected to MIMO radar matching filter processing, and calculating a signal covariance matrix; 3, employing a conventional subspace algorithm to achieve angle estimation of an incoherent signal source; 4, constructing a new Toeplitz matrix; 5, rejecting the incoherent signal source, and obtaining a covariance matrix of the coherent signal source; 6, employing an m-Capon algorithm to perform angle estimation of the coherent signal source, and estimating a direction of arrival of a target; and 7, estimating a direction of departure of the target. The coherent signal source MIMO radar angle estimation method in non-stationary noise achieves angle estimation of the coherent signal source.

The present invention provides a non-uniform sampling and reconstruction method of broadband multi-frequency sparse signals. The method comprises: calculating signal initial frequency spectrum information according to a multi-threshold energy detection system; establishing a signal sampling model through adoption of the non-uniform sampling parameter of rapid search emission search signals according to the obtained information; estimating signal frequency spectrum information through adoption of a subspace method of estimation; obtaining a rebuilt matrix unknown vector; and rebuilding an original signal. The method provided by the invention firstly adopts the multi-threshold energy detection system to estimate the signal frequency spectrum information and select an appropriate sampling period, so that the computation cost is reduced; and moreover, a frequency spectrum estimation algorithm based on a CAPON is adopted in the frequency spectrum estimation, so that the signal frequency spectrum information is rapidly estimated. Through adoption of the multi-threshold energy detection algorithm and the frequency spectrum estimation algorithm based on the CAPON, the computation complexity is further reduced, the frequency spectrum estimation speed in the non-uniform sampling is accelerated, and the numerical value robustness of the algorithm in a limited signal to noise ratio is ensured.

The invention provides an underwater target DOA (Directional of Arrival) estimation method based on an active virtual time reversal method. In a uniform linear array of a hydrophone, a detection acoustic source sends a signal, and a target receives the signal and reflects the signal. Each array element of the uniform linear array receives the signal and virtual time reversal is realized in a computer after filtering. After normalization processing, the time reversal signals are virtually transmitted to a channel as secondary transmission signals in the computer. Spatial smoothing is performedon secondary receiving signals and a covariance matrix of each sub-array is obtained respectively. A spatial spectral function of a Capon algorithm based on ADVTR (Active Detection on Virtual Time Reversal) is calculated and spectral peak searching is performed, and a spectral peak value is used as a DOA estimation value of the target. The invention reduces the energy attenuation of signals, improves the signal-to-noise ratio of the receiving signals, and can be directly extended to two or more targets.

The invention provides a noise suppression Capon active target DOA estimation method based on time reversal, which is different from most passive target DOA estimation. The method includes steps: an active target signal is received by employing a passive antenna array, namely the antenna array does not actively emit a signal detection space target but passively receives a signal emitted by an active target; when the antenna array receives the signal emitted by the active target, the signal is converted to receiving wave matrix forms for different channels, then time reversal and value back-transmission are performed, and a neural fuzzy reasoning system is adapted for noise suppression; and the noise suppression Capon active target DOA estimation method based on a TR is proposed, a space-time matching focusing characteristic of the TR and a specific direction optimization characteristic of a Capon algorithm are combined, and the estimation precision of a DOA is further improved. According to the method, multipath regarded as clutters is fully adopted, adequate receiving wave useful information is provided, and a result shows that an active target DOA spectrum obtained by employing the method has low sidelobe, high resolution and high precision, and the lower limits of the RMSE and the CRLB are lower.

The invention belongs to the field of radar signal processing, and discloses a no-fuzzy-parameter estimation method of a frequency diversity MIMO radar. The method comprises the steps of analyzing a relationship between a frequency increment and an element spacing which influence the traditional frequency diversity MIMO radar to form a distance-angle tight-coupling directional diagram, and designing a reasonable nonlinearly-increasing frequency increment; obtaining angle information of a target by transmitting a pulse of which the frequency increment is 0 and conducting Capon spectrum estimation; then transmitting a pulse of which the frequency increment increases nonlinearly, substituting the estimated angle information into a whole processing process, and combining the Capon spectrum estimation to obtain distance information of the target. According to the no-fuzzy-parameter estimation method of the frequency diversity MIMO radar, not only is the problem of distance-angle tight coupling of a frequency diversity MIMO radar transmitting directional diagram solved, but also the angle and no-fuzzy distance estimation of the target are achieved, and precise locating of the target is further achieved.

The invention provides a restraining method for direct path waves of a bi-static sonar system. The optimal weight is obtained by weighting an optimization model of a sparse constraint Capon wave beamformer; and a zero point is generated in the fixed direction of an array directional pattern through a zero point constraint wave beam forming technology, interference in the direction is eliminated,coherent interference is restrained, and thus the direct path waves are restrained. The bi-static sonar system is a bi-static configuration system, thus the receiving end can further receive the direct path waves with the amplitude being much larger than that of target echoes besides the target echoes. The deeper null can be generated beside the coherent interference, better tolerance can be achieved, low side lobes can be formed, and the capacity to SINR outputting by an array and steering vector angle mismatch resistance is improved.

The invention discloses a high-resolution distance image obtaining method. Aiming at a frequency modulated continuous wave radar, the method employs the Dechirp technology to achieve the transformation of the received frequency modulated continuous wave to a frequency domain, and employs a Capon method to achieve the recognition of target scattered points in distance, thereby obtaining the high-resolution HRRP of a target. The method can be used for forming a radar high-resolution one-dimensional distance image, and is good in application prospect because the introduced Capon method does not need order determination in advance.

The invention discloses an adaptive beam forming method based on maximum likelihood resampling. In the conventional process of inhibiting the influence of an interference signal, the influence of theinformation of an expected signal on the inhibition of the interference effect cannot be removed. The method comprises the steps: calculating a covariance matrix of M pieces of snapshot sample data ofa received signal; processing an estimated covariance matrix by using a particle filter and a beam space processing method to obtain an estimated noise and interference covariance matrix, calculatingthe maximum likelihood estimation corresponding to the matrix, selects h larger maximum likelihood estimations and a corresponding noise and interference covariance matrix; normalizing h estimationsto obtain a noise and interference covariance matrix weight; multiplying the obtained noise and interference covariance matrix by the noise and interference covariance matrix weight for addition to obtain a final estimated result, and bringing the final estimated result into a calculation formula of a beam forming weight vector to obtain the beam forming weight vector. Compared with a conventionalstandard Capon beam forming method, the method of the present invention can reduce the impact of the information of the expected signal on the inhibition of the interference effect.

The present invention belongs to the field of the radar signal processing technology, and discloses a signal arrival direction estimation method of the spectral function second derivative based on the minimum variance method. The method comprises: setting a radar uniform array, obtaining radar receiving data from the radar uniform line, and obtaining the steering vectors according to the radar uniform array; calculating the covariance matrix of the radar receiving data according to the radar receiving data, performing inversion of the covariance matrix, and obtaining the covariance inverse matrix of the radar receiving data; determining a Capon spatial spectrum function according to the steering vectors and the covariance inverse matrix of the radar receiving data; solving the second derivative of the Capon spatial spectrum function, and constructing a new spatial spectrum function according to the second derivative of the Capon spatial spectrum function; performing maximum likelihood estimation of the signal arrival direction according to the new spatial spectrum function, and obtaining the estimated value of the signal arrival direction; and improving the angular resolution and the robustness of the measure direction performance.

The invention discloses a capon operation table which comprises a table plate and a telescopic supporting frame, wherein the table plate is provided with a counting hole, fixed big clips, fixed small clips, a big upper clip moving hole, a big lower clip moving hole, a big lower clip pull wire hole, a small upper clip shifting activity slotted hole and a small clip fixing shifting slotted hole; and a main pull wire pedal rack drives a main pull wire to pull a main pull wire rod, a counter pull rod, a small upper clip pull wire rod and a big upper clip pull wire rod to operate a small upper clip, a big lower clip and a big upper clip of the table plate, so that the fixed big clips and the fixed small clips open or close simultaneously. When the capon operation table is not used, telescopic rod fixing bolts are loosened, the supporting frame, the table plate and a supporting plate are pushed and pressed, so that the capon operation table is placed and carried conveniently. The capon operation table is simple in structure, easy to assemble and disassemble, small in size, convenient to carry and use, easy to operate, high in efficiency, safe and reliable, can be used for castrating a large batch of chickens, is safe and effective for henneries and rural capon operators, and has high economic benefits and social benefits.

The invention belongs to the technical field of radars, and discloses a novel multi-channel SAR deception jamming identification and adaptive suppression method which can accurately identify, extractand suppress deception jamming. The method comprises the steps that a multi-channel SAR radar receives an echo signal, and distance-pulse compression and distance migration compensation are carried out on the echo signal; the azimuth FFT is transformed into the distance Doppler domain, and the difference between the ground object echo and the deception jamming in the space-time relationship is used to construct the airspace orthogonal weight vector of the ground object echo in the distance Doppler data domain Doppler channel by Doppler channel, and suppress a ground object echo signal; the residual after the suppression is detected Doppler channel by Doppler channel; the acquired interference Doppler channel is used to locate the interference distance along the distance direction; and finally, the acquired interference two-dimensional position is used to collect interference samples to estimate an interference covariance matrix, and a capon algorithm is used to carry out small-scale adaptive spatial filtering on an interference region.

The invention relates to the signal processing field for array antennas, in particular to a Capon robust self-adaptive beam forming method and a Capon robust self-adaptive beam forming system for mutual coupling errors. The beam forming system comprises a direction vector estimator, a sampler, a mutual coupling matrix former, a weight vector former and a beam former. The beam forming method of the beam forming system comprises the steps of data sampling, mutual coupling matrix acquisition, weight vector calculation, and steering vector and beam formation. The beam forming system and the beam forming method compensate for received array data by means of a mutual coupling matrix, correct the mutual coupling errors in the received array data, and improve the robustness of a self-adaptive beam forming algorithm; and the mutual coupling matrix corrects the mutual coupling errors of the array data, forms null in the direction of interference signals precisely, and improves an antenna gain ratio of a desired signal direction and the interference signal direction.

The invention provides a Capon beamforming-based positioning method and device. According to the Capon beamforming-based positioning method and device, K receiving antennas are set to form a signal receiving array, and M signal transmitting points are set; a covariance matrix Rxx is calculated by using a signal matrix outputted by the signal receiving array; the constraint optimization problem of the linearly constraint minimum variance criterion is solved, so that a spectral function can be constructed; M maximum spectral peaks are searched; and a direction of arrival is calculated. According to the method, beacon points deployed in a monitoring area are adopted to be networked with a wireless gateway so as to communicate with the wireless gateway; data are transmitted to a cloud end through a wireless communication module; cooperative sensing is performed, and the information of signal transmitting points in a network coverage area is acquired and positioned; the monitoring data of the cloud end are matched with a map and the like, so that intelligent parking can be realized. With the method adopted, the number of vehicles does not need to be known in advance or estimated, and therefore sampling data length can be decreased; desired signals are enhanced, interference is suppressed, and therefore, the signal to interference plus noise ratio of the output of a system can be improved; and a robust Capon algorithm is modified to improve the deviation of a direction vector from an actual environment, and therefore, positioning performance can be improved.

The invention discloses an adaptive beamformer design method based on a Bayesian compressed sensing algorithm, and the method comprises the following steps: (1) enabling a planar array element to receive a sound wave incident signal, wherein the sound wave incident signal comprises a target signal and an interference signal, constructing an adaptive beamformer based on the sound wave incident signal, and adopting the Bayesian compressed sensing algorithm to perform direction-of-arrival estimation on the sound wave incident signal; (2) reconstructing according to the direction of arrival of theinterference signal and the Capon spatial spectrum of the incident signal of the incident sound wave to obtain an interference and noise covariance matrix; (3) defining a maximum sidelobe horizontalconstraint value, constraining a sidelobe of the target beam pattern according to the maximum sidelobe horizontal constraint value, and calculating an array element weight coefficient of the adaptivebeamformer through a convex optimization method according to the interference and noise covariance matrix. And the output signal-to-interference ratio is higher.

The invention discloses a robust adaptive beamforming method for non-Gaussian signals in Gaussian noise. The method comprises the following steps: firstly, diagonally loading a four-order cumulant matrix of an array receiving signal, reconstructing a more accurate steering vector of an expected signal and interference through a series of processes based on a Capon four-order spatial spectrum loaded diagonally, and generating a virtual signal covariance matrix and a virtual interference covariance matrix; then, for array receiving signals, calculating a local Capon spatial cross-power spectrum,and estimating a noise covariance matrix; and finally, obtaining an optimal weight vector by utilizing the obtained expected signal steering vector, the virtual interference covariance matrix and thenoise covariance matrix, and forming steady adaptive beam output for array receiving signals. According to the method, a Capon four-order spatial spectrum, a Capon spatial cross-power spectrum and diagonal loading and neighborhood optimization technologies are utilized in a combined mode, a more accurate and effective steering vector and interference and noise covariance matrix of an expected signal is obtained, and the robustness of the self-adaptive beam former is improved.

The invention discloses an MIMO radar broadband DOA calculation method based on a sparse array in a clutter environment. The MIMO radar broadband DOA calculation method belongs to the field of singleprocessing, and specifically refers to WCSAB. According to the MIMO radar broadband DOA calculation method, clutter interference is suppressed by means of Capon beam forming, and then a target DOA isestimated by jointly using a CS method through utilizing different narrowband signal information. Considering that DOA estimation performance is not only related to a beamforming weight value, but also relates to a sparse array structure, the invention proposes a joint optimization problem of the beamforming weight value and the sparse array, and provides a simple algorithm to solve the optimization problem. According to the MIMO radar broadband DOA calculation method provided by the invention, the estimation performance including high resolution and low sidelobe of the target DOA in the clutter environment can be improved, the sparse array reduces the system cost and complexity, a Bayesian mean square error estimated by means of the target DOA is used as a performance evaluation index, and the sparse array structure designed by adopting the algorithm is similar to the optimal sparse array obtained through an exhaustion method in performance and is superior to a nested array and a co-prime array in performance.

The invention discloses an electrical impedance tomography method based on a spatial spectrum estimating algorithm. The method comprises the steps of forming a circular area by W electrodes; inputtingbrine into the circular area, injecting current into each set of adjacent electrodes of the W electrodes by means of a circulating adjacent exciting method, and performing voltage measurement on theelectrodes without injecting current for obtaining a first set of measured data; placing a to-be-imaged object into saline water, and obtaining a second set of measured data by means of a same method;establishing a circular domain model of W electrodes in simulation software, dividing the circular domain to N pixel block areas, expanding the circular domain and the electrodes, converting a resistance imaging model to a spatial spectrum estimating mathematical model, performing spatial spectrum estimation by means of a m-Capon algorithm, solving the strength of the spatial spectrum, and determining the pixel block with the to-be-imaged object according to the peak value of the spatial spectrum. The electrical impedance tomography method utilizes the m-Capon algorithm for performing spatialspectrum estimation and can improve imaging quality of the pixel block on the condition of relatively low electrical impedance change.