1325results about "Radio wave direction/deviation determination systems" patented technology

The invention discloses a target positioning method and system based on a single reference station, and relates to the field of wireless positioning, and the method comprises the steps: generating vortex electromagnetic waves carrying orbital angular momentum based on a transmitting end of a reference station, and generating a time-varying phase modulation transmitting signal and a metasurface time-varying coding sequence through a programmable metasurface; a time-varying phase modulation emission signal forms a multipath superposition effect in a propagation environment, a receiving end obtains a mixed signal of a direct wave and a reflected wave, and the receiving end carries out OAM mode separation on the mixed signal of the direct wave and the reflected wave through a spiral phase plate and an annular array to obtain signal components in different modes; and based on the signal component and the metasurface time-varying coding sequence, reconstructing an equivalent virtual array response by adopting a compressed sensing algorithm. According to the invention, the orbital angular momentum modal separation technology and the metasurface dynamic coding technology are creatively fused, and high-precision real-time direction finding in a complex multi-path environment is realized under a single base station architecture.

A covariance accumulation-based direction of arrival estimation method for an S-mode signal at a low signal-to-noise ratio, relating to the technical field of information processing. According to the method, a delayed covariance matrix of array output data is comprehensively utilized, a weight is determined by means of a correlation feature of the S-mode signal, and the delayed covariance matrix of array output data is accumulated, so that the direction of arrival estimation precision of a MUSIC method for the S-mode signal in a low signal-to-noise ratio environment is improved, establishing more accurate angle tracking for an S-mode target in the low signal-to-noise ratio environment, effectively reducing the false alarm probability, and expanding the effective working ranges of angle measurement and a tracking system.

The invention discloses a 3D underwater electric field source positioning method based on cross array arrival angle estimation, and belongs to the field of electromagnetic positioning detection. The method comprises the steps of setting two groups of receiving electrode array components, obtaining respective noise subspaces of an X-axis array signal and a Y-axis array signal, constructing a first spatial spectrum function of a signal source rotating around an X axis and a second spatial spectrum function of the signal source rotating around a Y axis, performing two-dimensional search based on the first spatial spectrum function and the second spatial spectrum function, and obtaining a two-dimensional search result. And according to the rotation mapping relation in the space coordinate system, solving and obtaining a 3D coordinate result of the signal source based on the search result. According to array symmetry and matrix operation invariance, a processing mode of imaginary axis-around arrival angle estimation based on a cross array is provided, three-dimensional space searching is converted into two-time two-dimensional plane searching, the dipole moment direction is simplified, and therefore rapid and accurate positioning of a near-field space signal source is achieved.

Disclosed in the present invention are a UWB-based positioning apparatus and positioning method for a point target of a pointing apparatus. The positioning apparatus comprises a pointing apparatus and a receiving apparatus, wherein UWB antennas are respectively arranged on the pointing apparatus and the receiving apparatus, and an accelerometer and a gyroscope are further arranged on the pointing apparatus. By means of the pointing apparatus and the receiving apparatus, UWB-based positioning is performed to obtain coordinates of the pointing apparatus in a coordinate system in which the receiving apparatus is located; then by means of the accelerometer, a motion vector of the pointing apparatus is obtained, such that a linear equation for a corresponding pointing direction of the pointing apparatus is obtained; and by means of solving an intersection point of the linear equation and a pointing area, coordinates of a pointing point are determined, thereby achieving a design purpose.

The invention discloses a single-bit direction of arrival estimation method and system with signal amplitude recovery, a terminal and a storage medium, and the method comprises the steps: obtaining each snapshot time signal from a signal source of a uniform linear array receiver, introducing a non-zero threshold value to carry out the single-bit quantization of each snapshot time signal, and obtaining a signal model; reconstructing the signal model, replacing a sign function of the reconstructed signal model with a smooth hyperbolic tangent function, and performing reconstruction to obtain a target signal model; based on the target signal model, constructing a single-bit DOA estimation optimization problem by using a truncated Frobenius norm and an L2, 0 norm, and converting the optimization problem into a target optimization problem by using a semi-quadratic technology; and solving a target optimization problem by using a near-end alternating minimization algorithm and a forward-backward splitting algorithm to obtain a signal source estimation direction, a signal source estimation number and a signal estimation amplitude. According to the method, the amplitude of the signal source is accurately estimated while the prior dependence on the number of the signal source is eliminated.

The invention provides a coherent signal arrival direction estimation method and device based on a deep convolutional network, and belongs to the field of array signal processing. The method comprises the following steps: receiving a to-be-detected signal containing a coherent signal by using a uniform linear array antenna to obtain an array receiving data matrix and extract a covariance matrix; forming an input feature vector by right upper triangular elements divided from a diagonal line in the covariance matrix, inputting the input feature vector into a covariance estimation model formed by a deep convolutional network, obtaining an estimation value of the right upper triangular elements under an ideal incoherent condition, and reconstructing the estimation value to obtain a covariance matrix estimation value; and performing characteristic decomposition on the covariance matrix estimation value, and generating a spatial spectrum by using a MUSIC algorithm to obtain an estimation result of the signal arrival direction. According to the method, the noise-containing mixed signal covariance matrix is mapped into the ideal incoherent noise-free signal covariance matrix through a physical constraint supervised learning framework, so that the estimation precision and robustness of the MUSIC algorithm in a coherent scene are improved.

A DoA estimation method and device based on steering vector matrix reconstruction, related to the field of array signal processing. The method includes: obtaining an array sampling covariance matrix according to an array received signal; setting a target variable, and limiting a feasible domain of the target variable by using two operators to determine a first constraint condition; characterizing an estimation error based on the target variable and the array sampling covariance matrix, and using the characterized estimation error as a second constraint condition; establishing an initial optimization model according to a preset norm based on partial sum of singular values and constraint conditions of the target variable; determining a multivariable optimization model according to the initial optimization model; and solving the multivariable optimization model to obtain an optimal result; analyzing the optimal result to obtain a DoA of the target incident signal.

Aspects presented herein may enable a user equipment (UE) to perform angle-of-arrival (AoA) determination using non-ideal and non-directional antennas. In one aspect, a UE obtains an indication of a phase difference of arrival (PDoA) function related to the first user equipment (UE). The UE obtains a set of PDoA measurements associated with a second UE when the first UE is associated with a plurality of orientations. The UE computes, based on the PDoA function, the set of PDoA measurements, and the plurality of orientations of the first UE, a general function that is associated with a probability in which the second UE is at a set of relative directions compared to the first UE. The UE estimates, based on the computed general function, a relative direction of the second UE compared to the first UE, where the relative direction is included in the set of relative directions.

The invention belongs to the technical field of array signal processing, and particularly relates to a co-prime array design method based on virtual array hole filling, which comprises the following steps of: S1, forwards moving two sub-arrays of an extended co-prime array by a distance of Nd / 2; s2, turning over one sub-array of the shifted co-prime array to obtain an improved co-prime array; s3, generating a differential virtual array according to the improved co-prime array; s4, introducing and combining the array to carry out hole filling on the differential virtual array; s5, calculating a received signal model and a covariance matrix of the filled virtual array; and S6, DOA estimation is carried out by using an ROOT-MUSIC algorithm. The method has the advantages that better signal source resolution and lower array element mutual coupling are achieved, meanwhile, the continuous freedom degree is improved, more signal sources can be estimated at the same time, and high practical value is achieved.

The invention discloses a periodogram and incoming wave direction finding fused multi-unmanned aerial vehicle signal identification method and system, and relates to a signal processing technology, and the method comprises the steps: obtaining to-be-identified signals with time domain aliasing and frequency domain non-aliasing; suppressing the noise of the to-be-identified signal by using an average periodogram method and smooth filtering, and calculating a bottom noise value; according to the calculated bottom noise value, setting a judgment threshold to detect a target unmanned aerial vehicle signal; estimating the start-stop frequency and bandwidth of the detected target unmanned aerial vehicle signal; performing signal separation by using an FIR filter according to the estimated starting and ending frequency and bandwidth; and executing incoming wave lateral direction based on the separated target unmanned aerial vehicle signal so as to complete signal identification. According to the method, unmanned aerial vehicle signal detection is completed through an average periodogram method, unmanned aerial vehicle weak signals which are sparsely distributed in space are further obtained through a direction finding method, and weak signal unmanned aerial vehicles which are far in distance are detected.

The invention belongs to but is not limited to the technical field of radio detection direction finding, and discloses a double-antenna three-dimensional rotating baseline direction finding method, device and system. Inter-channel phase deviation table compensation is carried out, equal-frequency-interval full-working-frequency-band measurement is carried out on phase deviation between two measurement channels in advance, and a channel phase deviation compensation table AB is formed; the compensation module is used for compensating inherent phase deviation between the channel A and the channel B; after the double-antenna three-dimensional rotating baseline direction finding device starts to work, a baseline formed by the antennas AB rotates anticlockwise at an angular velocity omega, two receiving channels synchronously collect data, and phase difference is calculated for the data corresponding to the baselines AB; based on a two-dimensional joint search method, through combination of coarse search and fine search, an azimuth angle and a pitch angle are estimated. According to the technical scheme provided by the invention, the direction finding range and reliability of a traditional system are greatly expanded, meanwhile, the cost is basically not increased, and the large-scale application of the technical system can be promoted.

The invention provides an AIS signal constrained least square angle estimation method, device and equipment and a storage medium, and the method comprises the steps: collecting time domain, frequency domain and phase domain TDOA observation data, and evaluating the observation precision of each path based on a signal-to-noise ratio, goodness of fit and phase stability; then, mapping multi-source observation values into a unified nonlinear observation equation, and constructing a weighting matrix according to each observation precision, so that a high-precision channel obtains a larger weight; thirdly, forming an equation and inequality constraint set by combining the physical incidence angle range constraint of the double / three-antenna array, the arrival time difference range constraint determined by the baseline length and the propagation speed and the three-antenna closed TDOA geometric constraint; and finally, constructing an optimization target in a constrained least square form, carrying out iterative solution through a sequential quadratic programming (SQP) algorithm, outputting an optimal angle estimation value on the premise of meeting all physical and geometric constraints, and realizing high-precision estimation of the AIS signal arrival angle in a complex electromagnetic environment.

The invention discloses a self-adaptive rotating baseline direction finding method, device and equipment, a medium and a terminal. Signals are continuously collected through the base line rotatable antenna array; rapidly identifying and outputting environment parameters by using the trained environment evaluation model, and evaluating the environment grade; constructing a dynamic direction-finding angle model by combining the attitude parameters and the motion parameters of the mobile platform, the control parameters of the antenna array and the environmental parameters; according to the environment parameters and the environment grades, a dynamic parameter optimization rule is formulated, and control parameters, direction-finding resolving parameters and signal processing algorithm parameters of the antenna array are adjusted; and based on the environmental parameters, the adjusted control parameters of the antenna array, the adjusted direction-finding resolving parameters and the adjusted adaptive filter parameters, calculating an incoming wave angle by using a dynamic direction-finding angle model. According to the method, high-precision incoming wave signal direction finding is realized in a dynamic environment, and the method is suitable for mobile scenes such as unmanned aerial vehicles and vehicle-mounted communication.

During signal reception, a tracking device includes a first antenna array configured to adjust a first steering angle of the first antenna array in a first plane and a second antenna array configured to adjust a second steering angle of the second antenna array in a second plane. The tracking device includes a phase difference of arrival calculator to determine a first phase shift between the first antenna array and the target device, a second phase shift between the second antenna array and the target device, and a phase difference of arrival between the first phase shift and the second phase shift. The tracking device includes a target device tracking circuit to determine the angle of arrival of the radiofrequency signal at the receiving device based on the phase difference of arrival.

The invention discloses a non-circular EBNC-PFLOM joint optimization DOA estimation method under impulse noise, and belongs to the technical field of array signal processing, and the method comprises the steps: firstly, through an array antenna of a dual-interproton array structure, receiving a received signal; secondly, respectively calculating an EBNC matrix and a PFLOM matrix by different order moment parameters based on a received signal; and finally, on the basis of the EBNC matrix and the PFLOM matrix, virtual array receiving signals are obtained through calculation, a covariance matrix is constructed, and a DOA estimation value is obtained through dimension reduction MUSIC. According to the method, efficient DOA estimation without spatial smoothing is realized, and the problem of performance degradation of a traditional method under non-Gaussian noise is solved.

The invention provides a sparse covariance reconstruction and adaptive grid correction-based DOA (Direction of Arrival) estimation method, and belongs to the technical field of ocean observation. According to the method, snapshot-level signal reconstruction is changed into covariance-level sparse modeling, an alternating optimization strategy is introduced to carry out energy estimation, a Sherman-Morrison matrix lemma is fused to accurately update a covariance inverse matrix, and an adaptive grid continuous correction mechanism is introduced. According to the method, a staged optimization framework is constructed, sparsity and geometric interpretability are fused, DOA estimation precision can be remarkably improved, off-grid error limitation is broken through, robustness under low signal-to-noise ratio and signal correlation is improved, algorithm calculation complexity is remarkably reduced, real-time processing capacity is improved, and the method is suitable for an underwater complex propagation environment.

Embodiments of the disclosed technology relate to improvements in location estimation and prediction for mobile devices while preserving energy. The use of classifiers is provided which preserves energy usage of the mobile device while providing contextually aware information for various stages. The use of a motion classifier and ranging in the context of access devices, the use of directional motion classifiers to reduce the latency in detection that a mobile device has entered a geofence area, and methods of improving location estimates and increasing geofence boundaries to prevent false exits from a geofenced area are disclosed.

The present disclosure relates to direction of arrival (DOA) estimation systems and super-resolution DOA estimation devices. An example system comprises a diffraction modulator configured to modulate phase distribution of electromagnetic fields of incident waves emitted by N signal sources to focus the incident waves on a detector, the DOAs corresponding to the signal sources within a preset angle range. The detector comprises a plurality of detection areas, the preset angle range comprising a plurality of angle intervals, each detection area corresponding to one angle interval. The detector is configured to measure intensity of an electromagnetic field in each detection area in response to the incident waves being focused on the detector to obtain an intensity measurement value of the electromagnetic field in each detection area, and determine the DOAs corresponding to the N signal sources based on angle intervals corresponding to N detection areas with greatest intensity measurement values.

The invention discloses an ultra wide band direction finding information extraction method based on a multi-input single-output delay superposition network. The method comprises the following steps: acquiring an antenna receiving signal and an attitude transformation matrix of an antenna; processing an antenna receiving signal to obtain a time point of a first peak leading edge detection threshold value and pulse sequence data in a complex form; carrying out 64-time up-sampling processing on the pulse sequence data in the plural form, and drawing an amplitude-time curve and a phase-time curve; determining a peak value corresponding to the adjacent antenna according to the peak value leading edge time point; calculating the peak values corresponding to the adjacent antennas to obtain the time difference of arrival and the phase difference of the adjacent antennas; and ultra-wideband direction-finding information positioning is realized. According to the invention, group delay can be carried out on the ultra-wideband pulse signal by adopting the delay line with the given length, and the ultra-wideband direction-finding information positioning precision is improved. The ultra wide band direction finding information extraction method based on the multi-input single-output delay overlay network can be widely applied to the technical field of ultra wide band positioning.

The invention relates to a mine monitoring method based on millimeter-wave radar multi-feature fusion, and the method comprises the steps: transmitting an FMCW signal through a millimeter-wave radar, receiving a target echo, sequentially carrying out the signal preprocessing, 1DFFT distance measurement, 2DFFT speed measurement, velocity ambiguity resolution and DOA estimation angle measurement, and extracting the distance, velocity, angle and energy variation features of a target point cloud; then millimeter-level deformation is obtained through phase analysis; obtaining a vibration frequency through band-pass filtering and spectrum analysis; fusing the six types of features of the target point cloud, adopting a confidence counter weighting decision mechanism, and triggering early warning when a fusion score exceeds a preset threshold value; according to the invention, through the advantages of high reliability, strong anti-interference performance and high non-contact safety of multi-feature fusion decision, the false alarm rate is significantly reduced, and the real-time accurate early warning capability of the mine dangerous state is improved.

The invention belongs to the technical field of wireless communication, and discloses a CNN-Transform direction estimation method based on covariance-unitary matrix input, and the method comprises the following steps: generating received signal sample data of different incident angles; calculating a covariance matrix for a received signal sample, performing singular value decomposition, extracting real parts and imaginary parts of the covariance matrix and a unitary matrix, and constructing a four-channel two-dimensional real number tensor as input; extracting local spatial features and coherence structures through CNN; serializing the feature map and adding a position code; a Transform encoder module is input, and global spatial dependence is modeled; carrying out average pooling and full-connection classification on the output to realize direction angle prediction; and training is carried out by adopting cross entropy loss, an AdamW optimizer and a cosine annealing learning rate scheduler. According to the method, local and global features are fused, and the method has high precision, strong robustness and excellent generalization ability in complex environments of low signal-to-noise ratio, multipath interference and the like.

The invention discloses a phase interferometer DOA and polarization parameter joint estimation method based on multiple linearly polarized antennas, and belongs to the technical field of radar signal processing. According to the method, the problems of low ambiguity resolution probability and low signal DOA and polarization parameter estimation precision of an existing method are solved. Noise variance and signal power estimation is carried out by adopting a method of receiving data covariance matrix high-order power, and the complexity is reduced. Aiming at the problem that the defuzzification probability is limited due to polarization mismatch, the method firstly adopts a method of solving a short base line by a long base line to reduce a phase difference error, then utilizes a multi-base-line phase weighted defuzzification method, and utilizes phase differences and amplitude information of all base lines to perform polarization domain phase difference and spatial domain phase difference decoupling, so that the defuzzification probability is limited. And the power estimation error is reduced through the LMMSE method, and the precision of signal DOA and signal polarization parameter estimation is improved. The method can be applied to joint estimation of DOA and polarization parameters of the phase interferometer.

The invention discloses a sparse regularization direction of arrival estimation method based on a risk minimization principle, and belongs to the technical field of array signal processing and underwater acoustic signal processing. The method comprises the steps of receiving array signals and establishing an observation model; constructing a sparse representation and over-complete dictionary; establishing and initializing a regularization optimization model; carrying out adaptive weight updating and risk-driven parameter selection; after regularization parameters are determined, a fast iterative shrinkage threshold algorithm FISTA is adopted to carry out optimization solution, and dictionary refinement is carried out on the detected direction after each iteration convergence so as to reduce off-grid errors; and after a small amount of outer layer iteration is repeated, outputting a final DOA estimation result and corresponding power. According to the method, self-adaptive selection of regularization parameters and noise levels can be realized, and the problem of precision degradation under complex conditions of low signal-to-noise ratio, limited snapshot number, signal source correlation, power imbalance and the like is effectively solved without manual parameter adjustment, so that the robustness and practicability of estimation are remarkably improved.

The invention discloses a multi-node mutual positioning method and system in a complex environment, each node can be set as a master node or a slave node, and the nodes realize a mutual positioning function by transmitting and receiving triangular wave frequency modulation continuous wave signal waveforms; when working in a master node mode, the node is synchronized with working signals of other slave nodes through coarse synchronization and fine synchronization steps, then distance information of the slave nodes is obtained through round-trip flight time calculation, distance information of the slave nodes is obtained through Doppler frequency shift calculation, angle information of the slave nodes is estimated through a DOA method, and positioning of the slave nodes is completed; when the node works in the slave node mode, a to-be-synchronized signal sent by the master node is waited, the to-be-synchronized signal is synchronized with the signal of the master node through the steps of coarse synchronization and fine synchronization, and then the synchronized signal is sent to the master node so that the master node can locate the position of the slave node. According to the method, high-precision mutual positioning among multiple nodes is realized through a working principle of realizing the frequency modulation continuous wave radar among the nodes.

A method for determining an angle of arrival and / or a direction of arrival of an electromagnetic wave from a mobile device to a receiving unit, in particular a UWB receiver. The receiving unit includes at least two receiving antennas, For determining the angle of arrival and / or the direction of arrival, a phase difference of arrival between signal responses at the receiving antennas is ascertained. The phase difference of arrival is ascertained at such a location in the signal responses that is still situated in the signal responses prior to a particular midpoint of a first signal path.

The application provides an angle of arrival measurement method, an electronic device, a readable storage medium and a chip, and relates to the technical field of wireless positioning. The method is applied to an electronic device, and the electronic device comprises a first antenna and a second antenna. The antenna radiation field patterns of the first antenna and the second antenna are similar within a first angle range around the electronic device and are not similar within a second angle range around the electronic device. The method comprises the following steps: determining the difference between target parameters measured by the first antenna and the second antenna according to a wireless signal; determining the angle of arrival range of the wireless signal according to the difference; wherein the angle of arrival range is the first angle range or the second angle range; and measuring the angle of arrival of the wireless signal by using the first antenna and the second antenna according to the angle of arrival range. The technical scheme provided in the embodiment can improve the accuracy of angle of arrival measurement.

Techniques are provided for steering vector generation. A methodology implementing the techniques according to an embodiment includes converting time domain data received from an antenna array to channelized frequency domain data. The method also includes receiving a request from a signal detection system, the request including a timestamp and duration of a detected signal of interest (SOI) and an indication that the SOI is pulsed or continuous. The method further includes generating, for a pulsed SOI, steering vectors to steer the antenna array to the pulsed SOI based on a segment of the time domain data stored in a first memory and identified by the time stamp and duration; and generating, for a continuous SOI, steering vectors to steer the antenna array to the continuous SOI based on a segment of the channelized frequency domain data stored in a second memory and identified by the time stamp and duration.

An embodiment receives a data stream comprising a plurality of sets of wave samples over a defined period of time, wherein receiving the data stream comprises receiving a transmitted signal at a receiver device from a transmitter device, and wherein the receiver device comprises an antenna array. The embodiment adjusts a beam shape at the receiver a number of times while the transmitted signal is being received during the defined period of time using the antenna array, wherein adjusting the beam shape a number of times produces a modulated plurality of wave samples based on different beam shapes. The embodiment determines the angle of arrival of the transmitted signal based at least in part on the modulated plurality of wave samples.

The invention provides a high-resolution DOA (direction of arrival) estimation method and system, and the method comprises the steps: updating a model covariance matrix based on a to-be-corrected space power spectrum and noise information of the iteration of this round, thereby obtaining a direction dependence weight factor, and carrying out the estimation of the direction dependence weight factor. And according to the direction dependence weight factor of the current round of iteration, the to-be-corrected spatial power spectrum, the model covariance matrix and the sample covariance matrix, predicting the to-be-corrected spatial power spectrum and noise information of the next round of iteration, and finally obtaining the spatial power spectrum. According to the method, on the premise that the number of prior information sources is not needed, the problem of spectrum peak merging of a traditional sparse method under the condition of adjacent information sources is solved, stable separation of near-angle incoming waves is achieved, and the high-resolution performance of DOA estimation is remarkably improved.

The invention relates to the technical field of navigation positioning, and discloses a satellite positioning method and device based on deep learning and filter coupling driving, and a medium. Determining a coarse positioning result of the receiver based on a least square method by using an observation pseudo-range between the receiver and each satellite and a model pseudo-range between the receiver and each satellite obtained by modeling; extracting observation quality features based on a coarse positioning result; inputting the observation quality features into a noise estimation model obtained based on deep learning to obtain a measurement noise covariance matrix and a noise compensation value; determining a state vector of a filter at an initial moment based on the coarse positioning result, and updating the state vector of the filter step by step based on the measurement noise covariance matrix and the noise compensation value to obtain a state vector at a to-be-estimated moment, the state vector at the to-be-estimated moment comprising a positioning result of the receiver at the to-be-estimated moment; noise and errors in the environment can be effectively compensated, so that the influence of the noise and the errors is effectively reduced, and the accuracy of satellite positioning is improved.