354 results about "Multiple signal classification" patented technology

A FMCW-type radar device generates snapshot data from a beat signal that represents a received condition of the radar device every modulation period. Auto-correlation matrices generated by the snapshot data every modulation period are averaged every set of plural periods. The radar device calculates the target azimuth of a target object such as a preceding vehicle based on the averaged auto-correlation matrix based on MUSIC (MUltiple SIgnal Classification) method. This averaging is performed by weighting average based on an amount of mixed noise (or an interference amount) contained in the snapshot data in each modulation period. A weighting coefficient to be applied to the auto-correlation matrix in each modulation period is set to a value corresponding to the amount of mixed noise, namely, the interference amount of this modulation period. The weighting coefficient becomes large when the interference amount is small, and on the other hand, becomes small when it is large.

The invention belongs to the field of radar technologies, and relates to a CE-OFDM (Constant Envelope Orthogonal Frequency-Division Multiplexing) based radar communication integration system. The invention is a CE-OFDM based super-resolution radar communication integration scheme which is provided on the basis of a traditional OFDM radar communication integration scheme, compensated through communication information, and capable of improving the effective data transmission rate and solving a problem that the PAPR of OFDM signals is too high. A transmitting terminal firstly turns data to be transmitted into CE-OFDM symbol frames through QAM (Quadrature Amplitude Modulation), IFFT (Inverse Fast Fourier Transform) and phase modulation, and a single pulse in a pulse repetition period is replaced by using a CE-OFDM symbol, so that the data transmission rate is improved, and the problem that the PAPR of transmitted signals is too high is solved. At a receiving terminal, received waveform pulses are demodulated, an inverse process of the transmitting process of the CE-OFDM system is carried out on the signals, and data can be demodulated; and the transmitting waveform is known, pulse compression processing is carried out on received echo waves, and super-resolution estimation for the distance and the speed of a target can be accomplished through decorrelation processing and an MUSIC algorithm after information compensation.

The invention relates to a multi-parameter combined estimation method based on bi-static FDA-MIMO radars. The method comprises the following steps: firstly designing a transmitting signal by utilizing characteristics of FDA and MIMO radars; carrying out matched filtering, vectorization and spatial smooth processing on a receiving signal; then estimating a combined steering vector and estimating a DOA and a speed parameter by utilizing an ESPRIT algorithm, and carrying out decoupling and parameter estimation on the DOD and distance information by combining characteristics of a transmitting waveform; and carrying out ambiguity resolution on a distance result estimated by utilizing an ESPRIT algorithm and combining a distance estimated by virtue of a pulse delay estimation algorithm, and carrying out ambiguity resolution on a speed by virtue of an MUSIC algorithm by combining signal characteristics of a large number of pulses. The method provided by the invention has the advantages that the problem that the distance and speed can not be accurately estimated under the condition of a single PRF can be effectively solved, and the estimation of the three-dimensional position and speed of a target can be realized; and a simulation result shows that the method provided by the invention has good estimation accuracy and stability.

The invention provides a method for estimating parameters of DOA (direction of arrival) and a distance of more near-field broadband signal resources by utilizing less array elements. The method comprises the following steps of: fully making use of characteristics of broadband signals, constructing a Toeplitz matrix by utilizing mutual correlation of outputs of array elements in a family of frequency on condition that array elements are less, wherein the Toeplitz matrix meets the conventional narrowband MUSIC algorism and comprises information about the DOA and the distance parameter; at last, estimating the DOA and the distance parameter by utilizing the MUSIC algorithm, thus realizing location of more near-field broadband signal resources. According to the method disclosed by the invention, location of more near-filed broadband signal resources can be realized by utilizing less array elements without parameter pairing, angle pre-estimation and broadband focusing, therefore, the method is lower in computational load and convenient for a practical application.

The invention provides an anti-interference method of GNSS (global navigation satellite system) receiver equipment. The anti-interference method adopts spatial spectrum estimation MUSIC (multiple signal classification) algorithm, thus having good anti-interference effect. Different from traditional power inversion algorithm, the spatial spectrum estimation MUSIC algorithm distributes banded nulls near an interference source. The anti-interference method can accurately find the interference direction and can effectively restrain the interference; even if the signal to interference ratio is reduced to be 20dB, the anti-interference method can also restrain the interference.

The invention is a DOA estimating method to realize circle-angle positioning based on TD-SCMDA standard, firstly adopting multiple signal classifying and correcting algorithms to realize the DOA estimation of intelligent antenna circle-angle positioning; aiming at TD-SCMDA antenna being uniform circle array, converting the array cell-space uniform circle array into mode-space virtual uniform line array; according to eigenvalue and eigenvector characteristic of the data covariance matrix of the virtual line array, advancing a MUSIC algorithm based on mode-space virtual uniform line array and deriving the MUSIC algorithm power chart for the virtual line array and the general implementation algorithm for the mode-space MUSIC algorithm; according to the character of MUSIC algorithm inapplicable to the DOA estimation of relative signal source, advancing the correcting MUSIC algorithm based on the mode-space virtual uniform line array; finally aiming at the problem that the array aperture is small and that the resistance to array cell error disturbance is bad, caused by MUSIC algorithm, advancing four-order cumulant MUSIC algorithm and four-order cumulant correcting MUSIC algorithm based on the mode-space virtual uniform line array.

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

The invention discloses a rapid two-dimensional spectral-peak searching method suitable for engineering realization. The method comprises the following steps of: 1, carrying out two-dimensional global search for a spatial spectrogram composed of a noise subspace and antenna array flow pattern vectors, and obtaining global search spectral-peak points; 2, carrying out fine search near the global search spectral-peak points, and obtaining spectral-peak candidate points; 3, classifying the spectral-peak candidate points, and finding real spectral-peak points corresponding to the number of signals; and 4, and utilizing false spectral peak information around a real spectral peak, and finally using a weighted value of the real spectral peak and false spectral peaks around the real spectral peak as an estimated value of an incoming wave direction. Aiming at using a 2D-MUSIC algorithm to estimate the direction of arrival of incident signals, a two-dimensional spectral-peak searching process occupies most of the time of the whole algorithm so as not to obtain the direction of arrival of the signals in real time or on time. According to the method disclosed by the invention, on the basis of characteristic analysis of the spatial spectrogram, a data cluster and grading searching method is used to accelerate the spectral-peak searching process and the precision of search results are ensured.

The invention discloses an adaptive high-precision phase estimation method for an interferometric SAR, comprising the following steps of: structuring optimum weight vectors in combination with a Wiener filter theory, performing an eigen decomposition on an optimum covariance matrix composed of the optimum weight vectors to obtain a signal subspace and a noise subspace, adequately utilizing a corresponding pixel pair and the coherent information of the neighboring pixels thereof to structure a space spectrum function according to the orthogonality of the signal subspace and the noise subspace in a MUSIC (multiple signal classification) algorithm, and precisely estimating the interferometric phase between the corresponding pixels via a spectral peak searching. The optimum weight is obtained by only a Wiener filter without the need to determine a registration error and the direction thereof, thereby solving the problem of large computational burden in the traditional InSAR (interferometric synthetic aperture radar) interferometric phase estimation. The adaptive high-precision phase estimation method for the interferometric SAR disclosed by the invention is adaptive to the field of accurate surface parameter inversion of InSAR complex scene and the like.

The invention relates to an accurate direction-finding device and way for P, L wave-band radiation source, which comprises an antenna array comprising 6 array elements and 6 corresponding receivers, a signal processor and a calibrating signal source. Microwave emitted from an object in the space will be received by the 6 antennas, and sent into 6 microwave receivers behind the antennas, then sent into a digital receiver through the frequency converting and amplification by a hi- / middle-frequency and a mid-frequency receiver; the digital receiver will extract the phase values of the 6 signals through a hi-speed A / D converter and send them into the signal processor, which works out the incident angle Theta of the signals by using a space spectrum evaluating arithmetic MUSIC. The invention realizes hi-accuracy direction finding for P, L wave-band radiation source.

The invention discloses a radar target two-dimensional imaging method based on vortex electromagnetic waves. The radar target two-dimensional imaging method is based on an echo model of ideal scattering points under projection of the vortex electromagnetic waves generated by a uniform loop antenna array, performs orbital angular momentum (OAM) mode sampling on radar target echo signals and calculates a related function, adopts a multiple signal classification (MUSIC) algorithm to obtain a spatial spectrum function, and carries out two-dimensional spectrum peak searching to realize two-dimensional joint detection of a pitch angle and an azimuth angle of a radar target. Compared with a traditional direction-of-arrival (DOA) estimation scheme based on a plane wave MUSIC algorithm, the radar target two-dimensional imaging method provided by the invention can realize higher angular resolution; and compared with an existing radar target azimuth angle imaging scheme based on vortex electromagnetic waves, the radar target two-dimensional imaging method can realize the imaging of the target pitch angle without increasing hardware cost, and is of great reference significance to the modern radar design of the new system.

The invention provides a method for measuring tree heights by a tomography synthetic aperture radar (SAR) based on compression multi-signal classification (CS-MUSIC). The method solves the problem that the aerial photography frequency is high in traditional SAR tomography, an echo observation vector matrix is established by using the correlation among all polarization channel signals of the complete polarization SAR, and the CS-MUSIC algorithm is used for conducting elevation scattering coefficient reconstruction. Compared with a traditional spectrum estimation SAR tomography method, the number of false targets can be decreased in the method, and meanwhile the aerial photography frequency needed by the tomography SAR in the tree height measuring process is lowered.

The invention relates to the technical field of radars, in particular to the application of a single base MIMO (Multiple Input Multiple Output) radar system and a compression spatial spectrum-based single base MIMO radar target DOA (Direction of Arrival) estimation method. The compression spatial spectrum-based single base MIMO radar target DOA estimation method comprises the steps of enabling an emission array to emit phase-coded signals which are mutually orthorhombic and enabling a receiving terminal to perform matched filtering processing through a receiving array matching filter; performing dimensionality reduction processing on J receiving data subjected to snapshotting matched filtering through a dimensionality reduction array; calculating a covariance matrix R of the receiving data Y subjected to dimensionality reduction processing and working out an intersection subspace of a noise subspace and a conjugate subspace thereof; constructing a compression spatial spectrum function and searching the compression spatial spectrum function; excluding a false DOA and obtaining a real DOA of a target. The compression spatial spectrum-based single base MIMO radar target direction of arrival estimation method avoids a combined search of a two-dimension DOA of a traditional MUSIC algorithm when searches the airspace DOA, and only needs one-dimensional space search and the algorithm complexity is reduced.

The invention relates to an error estimation method in wave-reaching direction estimation and in particular to a method of correcting various array errors in wave-reaching direction estimation. In order to overcome the defects that the processing speed is relatively low and the complexity is relatively high as an existing array error processing method always corrects one error, the invention provides the method of correcting various array errors in wave-reaching direction estimation. The method comprises the following steps of: acquiring an amplitude and phase error matrix and a cross coupling array; obtaining a characteristic decomposition covariance matrix, a noise sub-spatial matrix and an estimation matrix according to a MUSIC algorithm; defining a spatial spectrum; searching for DOA estimation of N peak values in the spatial spectrum; solving an estimated value of an amplitude and phase inconsistency error matrix; solving an estimated value of the cross coupling matrix; calculating a cost function; giving a threshold, and if the difference between the adjacent iterated cost functions twice is greater than the threshold, performing continuous iteration; and if not, escaping circulation to obtain a to-be-estimated parameter. The method provided by the invention is suitable for estimating the wave-reaching direction in the presence of the array error.

The invention provides a monostatic expansion co-prime array MIMO radar DOA estimation method based on a MUSIC algorithm. Firstly, a traditional co-prime array is expanded according to two opposite directions to obtain an expanded co-prime array; the expanded co-prime array is respectively used as a transmitting array and a receiving array of the MIMO radar to transmit and receive signals; the whole receiving array is used as a whole, DOA estimation is carried out by using the receiving data of all receiving array elements, and the self-information and mutual information of the array are simultaneously utilized, so that the degree of freedom and the DOA estimation precision are greatly improved compared with those of a traditional co-prime array DOA method. A traditional co-prime array DOAestimation algorithm usually cannot strictly eliminate the phase ambiguity problem, and due to the fact that MIMO radar is introduced into the algorithm, the condition for generating phase ambiguityis extremely strict, and the algorithm is strict and free of phase ambiguity.

The invention provides a compressed spectrum sensing method based on autocorrelation matrix reconstitution and mainly solves the problem that an existing sensing algorithm is high in sampling speed and large computation overhead. The compressed spectrum sensing method comprises that a secondary user obtains an observation sequence of a frequency spectrum environment through compressed sensing and obtains an autocorrelation matrix estimated value of Nyquist sampling by utilizing autocorrelation vector quantity of a autocorrelation matrix reconstitution Nyquist sample sequence of the observation sequence; a multi-signal classification MUSIC algorithm is adopted to obtain an estimated value of occupied channel number according to a characteristic value of the autocorrelation matrix estimated value; a characteristic spectrum is constructed according to the characteristic value and the estimated value of the occupied channel number, spectral amplitude values corresponding to characteristics of channels are added to obtain a sum, and mark numbers of the occupied channels are judged. By means of the compressed spectrum sensing method, the sampling speed of a secondary user receiving machine can be reduced, algorithm complexity at the reconstitution end is low, and spectral amplitude occupying situation in a cognitive radio system can be judged quickly.

The invention relates to a direction estimation method of an MIMO-UKF-MUSIC (Multiple Input Multiple Output-Unscented Kalman Filter-Multiple Signal Classification) target. In the actual direction finding process, according to an MUSIC spatial spectrum estimation algorithm, fluctuating target signal-to-noise ratio and time-varying strong interference commonly occur, radar signals of a plurality of targets of an MIMO sky wave radar are coherent signals, the disadvantageous conditions need to be deeply analyzed, and the estimation performance of an MUSIC algorithm under non-ideal conditions is improved. The direction estimation method comprises the following steps of 1, acquiring a plurality of groups of DOA (Direction of Arrival) estimation values and a plurality of groups of DOD (Direction of Departure) estimation values in a plurality of sensor arrays under an MIMO system; 2, filtering the DOA estimation values and the DOD estimation values respectively to obtain a plurality of groups of DOA estimation filtering values and a plurality of groups of DOD estimation filtering values, and averaging the plurality of groups of DOA estimation filtering values and the plurality of groups of DOD estimation filtering values to obtain final DOA estimation and final DOD estimation. The direction estimation method of the MIMO-UKF-MUSIC target is applicable to the field of array signal processing.

The invention discloses a frequency spectrum perceiving method based on the estimation of a signal arrival direction, which comprises the steps: in a cognitive radio system to which smart antenna technology is applied, the direction and the angle of signal transmission are used as a frequency spectrum opportunity, and a master user signal is subjected to two-step perception: firstly, the master user signal is detected by using a method based on a generalized likelihood ratio test, namely that the ratio of the maximum eigenvalue to the sum of the eigenvalues of a sample covariance matrix is used as test statistics; the test statistics are compared with a decision threshold which is set according to a given false alarm probability so as to decide whether the master user signal exists or not; if a master user does not exist, then the channel can be used, and if the master user exists, then a classical MUSIC (Multiple Signal Classification) algorithm is further used to estimate the arrival direction of the master user signal. A cognitive user can select other directions for communication, which do not cause disturbance to the master user, and the frequency spectrum perceiving method can effectively perceive time, frequency and the frequency spectrum vacancy of a space domain, perceive the frequency spectrum vacancy of an angle domain, and increase the frequency spectrum opportunity.

The invention discloses a micro-motion target scattering point track association method based on a distance-instant Doppler image. The method comprises the following steps of (1) receiving an inverse synthetic aperture radar echo; (2) carrying out inverse synthetic aperture radar echo pretreatment; (3) through the distance-instant Doppler image, acquiring a two-dimension coordinate of a micro-motion target scattering point; (4) carrying out two-dimension track association; (5) using a rooting multiple signal classification Root-MUSIC method to correct a track matrix; (6) acquiring a track association result of the micro-motion target scattering point. A domain associated to the scattering point is converted into a slow time-distance-instant Doppler domain with a high separability from a distance-slow time domain; separability of the micro-motion target scattering point is enhanced; for complex motion forms of spinning, processional motion, nutation and the like, advantages that universality is possessed, track association precision is high, an association error is small and so on are achieved; forceful guarantee can be provided for subsequent high-resolution imaging and target feature extraction.

The invention provides a DOA estimation method considering a mutual coupling effect under a non-uniform noise condition. The method includes the following steps: firstly, an algorithm obtains a noise-free signal covariance matrix under mutual coupling conditions through an alternating iterative method based on a least square theory; then, a mutual coupling coefficient matrix can be reconstructed by using a signal subspace principle to solve the noise-free signal covariance matrix after mutual coupling compensation; and finally, decoherence of coherent signal sources can be realized based on aspatial smoothing method, and DOA parameter estimation can be achieved by using a traditional MUSIC algorithm. Numerical simulation shows that compared with the traditional DOA estimation algorithm under the MUSIC, non-uniform noise and mutual coupling condition, the provided algorithm can better inhibit non-uniform noises, obviously relieve the influence of the mutual coupling effect on the spatial smoothing algorithm, and obviously improve DOA estimation performance under coherent signal source conditions.

The invention provides a ranging passive location method under an azimuth angle prior condition based on linear sparse arrays. The features of a multi-station system and a single-station system of passive location are combined, on the basis that observing stations are arrayed in a small space range in a linear sparse array mode, the observing stations are used for receiving data phase information, and near-field radiation source ranging location is achieved. On the basis of meticulous analysis of a structure of observed data phase information, prior azimuth angle information is used for carrying out phase compensation on a phase fuzzy part existing in the observed data phase information, a non-phase fuzzy part existing in the observed data phase information is used for establishing an array signal model, and estimation of near-field radiation source distance is completed based on a MUSIC algorithm.

The invention belongs to the signal processing field and relates to a receiving signal covariance matrix rank minimization direction-of-arrival (DOA) estimation method based on a spatial smoothing method. The invention aims to solve the problems of low angle estimation poor accuracy and low resolution of a traditional direction-of-arrival (DOA) estimation method under a condition of coherent signals and non-uniform noises. According to the receiving spatial covariance matrix rank minimization direction-of-arrival (DOA) estimation method based on the spatial smoothing method of the invention, on the basis of the traditional spatial smoothing method, a receiving signal covariance matrix is pre-multiplied and post-multiplied by an exchange matrix separately, so that a spatial backward smoothing covariance matrix can be obtained; the covariance matrix is reconstructed to be a noiseless covariance matrix based on the low-rank feature of the smoothing matrix; and finally a traditional MUSIC(multiple signal classification) algorithm is adopted to achieve DOA estimation. Numerical simulations show that the algorithm provided by the invention can better suppress the influence of non-uniform noises and has high DOA estimation performance under a coherent condition compared with traditional MUSIC, MC-MUSIC and RTM algorithms.

The invention discloses a two-dimensional MUSIC (multiple signal classification) direction-detecting device for a uniform circular array, which comprises an FPGA (field programmable gate array) processing unit and a DSP (digital signal processor) processing unit, wherein the DSP processing unit is used for receiving a covariance matrix containing target azimuth information sent by the FPGA processing unit, utilizing a two-dimensional MUSIC algorithm to obtain the target azimuth information and sending the target azimuth information to the FPGA processing unit, and the FPGA processing unit is used for performing filtering noise-removing treatment on a signal received by an external antenna, and then calculating the covariance matrix containing the target azimuth information and storing the azimuth information calculated by DSP. According to the device, the two-dimensional MUSIC algorithm serves as a method for estimating the target azimuth, the calculating complexity in each step is reduced as much as possible, and the real-time direction-detecting capacity of the device is higher than that of the traditional device.

The invented near-field correction method includes the following steps: utilizing position information of radar antenna array and high-frequency sea-state radar marine echo characteristics to detect marine echo with single-bearing arrival angle, and utilizing single-bearing arrival angle marine echo and multiple signal classification algorism to estimate channel amplitude mismatch factor to implement amplitude correction; utilizing near-field single auxiliary signal source set on the extended line of antenna array and utilizing amplitude-corrected single-bearing arrival angle near-field arrival wave signal, position information of array unit antenna, bearing information of near-field auxiliary source and multiple signal classification algorism to estimate and obtain mismatch factor of channel phase so as to implement phase correction.

The invention discloses a double sound source localization method based on a consistent focusing transform least square method. According to the method, a predesigned six-element circular microphone array is applied to acquire sound source signals, and the covariance matrix of the acquired signals is acquired; a focusing transform matrix is defined by utilizing the center frequency point of frequency range, and the focusing transform matrix is solved by the least square method; and a signal spatial spectrum corresponding to each center frequency point is acquired by utilizing the center frequency points of different bandwidths, a consistent focusing matrix and a multiple signal classification method, and then the average estimation value of the signal spatial spectrum is obtained by utilizing the average value of the frequency points and a time snapshot estimation method (MUSIC) so that a sound source azimuth angle estimation value is acquired. The method is high in sound source localization estimation accuracy so that an azimuth ambiguity problem can be effectively overcome.

The invention discloses a method for MIMO radar system angle estimation based on fast Fourier transformation. The method for MIMO radar system angle estimation based on fast Fourier transformation comprises the steps that a data matrix received by a first pulse of the radar system is evenly divided and divided signals are expressed in the description, new signals are divided by the four matrix blocks defining; bi-dimensional fast Fourier transformation is respectively conducted to the signals shown in the description; coherent integration is conducted on F11(l), F12(l), F21(l) and F22(l), a peak point shown in the description and the corresponding subscript ix and the corresponding subscript iy are recorded, points corresponding to the subscript ix and the subscript iy are respectively obtained from the F11(l), the F12(l), the F21(l) and the F22(l), so that the vector of f(1) belonging to C4*1 is established; the covariance matrix of the f(1) is calculated according to the sampling covariance matrix inversion principle, characteristic decomposition is conducted on the covariance matrix, and a noise projection matrix pn can be obtained through a noise sub space un; a transmitting oriented vector and a receiving oriented vector br(theta) are obtained according to a receiving data matrix Y(1) and the leaving angle and the reaching angle are estimated through the MUSIC arithmetic.

The invention relates to a dynamic tracking method of the direction of arrival of coherent signals under an impulsive noise environment. The dynamic tracking method comprises the steps that signal sampling data are acquired; classifying unification preprocessing is conducted on a received signal data vector; a uniform linear array is divided into a plurality of subarrays; a received data vector undergoing spatial forward backward smoothing is substituted into a PASTA algorithm to obtain signal subspace; a MUSIC algorithm is used for processing the data of the signal subspace, and the direction of arrival of object signals is acquired through spectral peak searching; a t is made to be equal to t+1, the angle of the direction of arrival of the signals with corresponding the beat number is obtained until the maximum beat number is reached, and DOA dynamic tracking of coherent signal sources under the impulsive noise environment is achieved. According to the method, a projection subspace approaching tracking algorithm is used, the signal subspace of incident signals can be tracked in real time, then a MUSIC method is used for conducting precise detection on the direction of arrival of the signals, the robustness of the method is high, and the tracking effect is good.

The invention provides a single dipole polarization sensitive array dimensionality reduction DOA estimation method in a multipath interference environment. The array employs single dipoles concurrent with the edge of a circumference to from a uniform circular array structure, can simultaneously perform azimuth angle and elevation angle two-dimensional estimation and can effectively fight multi-path interferences to realize mathematical modeling of narrowband signals received by a uniform circular array concurrent array; then according to a matrix rank loss principle, the four-dimensional spectral function of the polarization MUSIC (multiple signal classification) algorithm is subjected to dimensionality reduction processing to construct a spatial spectral function so as to realize the fast search of spatial two-dimensional angles. Compared with polarization sensitive array DOA and polarization parameter combined estimation methods, the dimensionality reduction DOA estimation method of the invention can realize rapid estimation of signal source angles under the condition of not increasing hardware demands, receive and utilize the polarization characteristics of signal sources and interference sources to effectively distinguish objects and interferences to realize object estimation in a complex environment and has a certain engineering application value.