120results about "Multi-channel direction-finding systems using radio waves" patented technology

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.

METHOD FOR DETECTING A DRONE AND ITS REMOTE PILOT AND SYSTEM FOR IMPLEMENTING IT Method (500) for detecting a drone (21) and / or a remote pilot (22) in a monitored area (300), said method comprising an acquisition step (510) on at least one receiver (111) of a plurality of frames of a digital signal (yn, y'n) to be analyzed, said method comprising the following steps: (513) digital frequency filtering of the digital signal (y'n) in narrow frequency bands (wk) producing a number K of filtered digital signals (zn,k); (521) estimation of the energy levels (Ek) of the filtered digital signals (zn,k) obtained in the digital filtering step (513); (523) construction of a time-frequency state matrix (SM) of the energy levels (Ek) ;(524) calculation of a transition matrix (MT), based on a first-order derivative of the state matrix (ME) ;(525) calculation of an average rate of change (α) of the transition matrix (MT);and (526) detection of the presence of the drone (21) and / or the remote pilot (22) as a function of the value of the average rate of change (α). Figure of the abstract: Figure 1;

The invention discloses a large-scale MIMO multi-satellite positioning and direction estimation method and system based on angle information. The method comprises the following steps: firstly, obtaining channel matrix estimation between each satellite and a user by sending a pilot signal; then, obtaining estimated values of channel parameters by using a tensor-ESPRIT algorithm, wherein the estimated values comprise an angle of departure and an angle of arrival; according to the estimated departure angles, direction vectors between the user and all satellites are obtained, an optimization problem on spherical manifold is established, altitude constraints are considered, and a Riemann conjugate gradient method is used for solving and obtaining a user position estimation value; and finally, according to the estimated user position and arrival angle, establishing an optimization problem on the SO (3) manifold, and solving by using a Riemannian gradient descent method to obtain an estimated value of a user array rotation matrix. According to the method, positioning and direction estimation are performed by combining channel information between a plurality of satellites and users, and altitude constraints are considered during positioning, so that compared with single-satellite and non-constraint conditions, the positioning performance can be remarkably improved, and meanwhile, the method has good direction estimation performance.

A method to perform localization is disclosed. The method may be performed by a first device of a plurality of devices distributed non-uniformly in a network. Each device, from the plurality of devices, may be configured to detect or obtain signals from an emitter. The method may include obtaining signals from the emitter and converting the signals into a first complex amplitude. The method may further include broadcasting the first complex amplitude to one or more second devices of the plurality of devices. The method may further include obtaining, by the first device, a second complex amplitude from the second devices, and constructing a correlation matrix based on the first complex amplitude and the second complex amplitude. The method may additionally include determining a line of bearing to the emitter based on the correlation matrix, and determining an emitter location based on the line of bearing.

A method, a sensor system, and a non-transitory computer readable medium are provided to determine the angle of arrival of signal 300 reflected of a target object 302. The method involving receiving a plurality of incident signals reflected from a target at a plurality of receiver antennas 304, identifying with a processor a subset of receiver antennas (404. Fig 4) from the plurality of receiver antennas when the target is in a near filed of the plurality of receiver antennas. The processor performs angle of arrival (AOA) processing on respective incident signals of the subset of receiver antennas to determine the angle of arrival of the signal. The method preferably determining an elevation and azimuth angle of the target based on the angle of arrival. The plural antenna are preferable part of a switched antenna array. The receiver antennas preferably being part of a multiple input multiple output (MIMO) radar and the subset corresponds to a virtual array formed by the MIMO radar. Preferably using all the plurality f antennas to perform AoA determination when the target is determined to be in the far field of the radar.

The application discloses a two-dimensional Root-MUSIC angle automatic pairing method and system based on signal receiving timing, and specific steps of the method are as follows: step 1, a Root-MUSIC algorithm mathematical model suitable for angle estimation of two orthogonal arrays of an L-shaped array is constructed, the Root-MUSIC algorithm is applied to the two orthogonal arrays respectively, and a set of azimuth angles and a set of elevation angles are estimated; step 2, timing detection and dynamic grouping are carried out based on signal arrival timing, and simultaneous multi-signal receiving processing is converted into a single-signal processing flow organized according to timing; the Root-MUSIC algorithm is executed on each group of signals, and pairing of the azimuth angles and the elevation angles is automatically completed; and step 3, the pairing result of step 2 is stored, and whether the pairing process is ended is judged, if yes, the angle pair is output in sequence. The application constructs a joint processing mechanism of timing detection-dynamic grouping-serial processing, converts traditional multi-dimensional matching calculation into a simple timing alignment operation, and makes angle pairing become a natural derivative result of the signal processing flow.

The present invention relates to an indoor positioning system 300 for a wireless communication network 200. The indoor positioning system 300 includes one or more anchor devices 302a-302n, a central entity 306, and one or more tag devices 304a-304n. Transmission of signals 301a-301n by the one or more tag devices 304a-304n is controlled so that one signal 301a is transmitted at a time on a given radio resource, and the tag device 304a transmitting one signal 301a is the tag device 304a to be located. At least one anchor device (302a) of the one or more anchor devices (302a-302n) is configured to receive, via an antenna array (500), a signal (301a) transmitted by a positioned tag device, determine an estimate of a direction of arrival (DOA) based on the received signal (301a) by applying a first power law based algorithm and a second power law based algorithm, respectively, and transmit the estimated DOA together with DOA metadata to a central entity (306). The present invention also relates to an indoor positioning method, an anchor device, a computer program, and a computer-readable medium.

Techniques are provided for jammer detection. A methodology implementing the techniques according to an embodiment includes estimating an angle of arrival of a jamming signal, the jamming signal included in a received signal, and generating a direction finding (DF) confidence indicator associated with the estimated angle of arrival. The method also includes extracting the jamming signal from the received signal. The method further includes correlating the extracted jamming signal with previously extracted jamming signals to generate a correlation score and using the correlation score as a uniqueness assessment of the extracted jamming signal. The method further includes identifying characteristics of the extracted jamming signal and generating a characterization confidence indicator. The method further includes demoting the extracted jamming signal to non-jammer status based on one or more of the DF confidence indicator, the uniqueness assessment, and the characterization confidence indicator.

A method, a sensor system, and a non-volatile, computer-readable medium are provided. Embodiments include receiving a plurality of incident signals reflected from a target at a plurality of receiver antennas. A processor identifies a subset of receiver antennas from the plurality of receiver antennas and performs angle-of-incidence (AOA) processing on the respective incident signals from the subset of receiver antennas. The processor determines the angle of incidence of the target based on the AOA processing.

A wave source location direction estimation apparatus (3) includes: a signal acquisition unit (21) to acquire a reception signal of one or more radio waves from an antenna (11) to receive the one or more radio waves from among a direct wave which is a radio wave from a wave source (1) and one or more multipath waves which are radio waves from the wave source (1); and a profile calculation unit (22) to calculate an angle profile including directions of incidence of the respective radio waves on the antenna (11), and reception power levels of the respective radio waves on the basis of the reception signal acquired by the signal acquisition unit (21). In addition, the wave source location direction estimation apparatus (3) includes a direction estimation unit (23) to estimate a direction in which the wave source (1) is located on the basis of the angle profile calculated by the profile calculation unit (22).

Methods and systems for spatial filtering transmitters and receivers capable of simultaneous communication with one or more receivers and transmitters, respectively, the receivers capable of outputting source directions to humans or devices. The methods and systems use spherical wave field partial wave expansion (PWE) models for transmitted and received fields at antennas and for waves generated by contributing sources. The source PWE models have expansion coefficients expressed as functions of directional coordinates of the sources. For spatial filtering receivers a processor uses the output signals from at least one sensor outputting signals consistent with Nyquist criteria representative of the wave field and the source PWE model to determines directional coordinates of sources (wherein the number of floating point operations are reduced) and outputs the directional coordinates and communications to a reporter configured for reporting information to humans. For spatial filtering transmitters a processor uses known receiver directions and source partial wave expansions to generate signals for transducers producing a composite total wave field conveying communications to the specified receivers. The methods and communications reduce the processing required for transmitting and receiving spatially filtered communications.

The present disclosure relates to a method (100) for determining an angle of arrival, AoA, of received radio frequency, RF, measurement signals. The method comprises obtaining (101) measurement data based on the received RF measurement signals from an antenna array, wherein the RF measurement signals are representative of multiple frequency channels. The method further comprises determining (102) power spectra, comprising determining at least one power spectrum for each of the multiple frequency channels by using the measurement data. The method further comprises providing (105) a machine learning algorithm, which is pre-trained to determine an AoA based on power spectra of multiple frequency channels. The method further comprises determining (106) the AoA of the received RF measurement signals by using the machine learning algorithm and the determined power spectra.

The present invention belongs to the field of communication positioning technology, and specifically relates to a GPS positioning and 4G communication service system for an Internet of Things device, including: a data transceiver module for data communication between a device and a server, and bidirectional data transmission through a 4G communication base station; a channel environment classification module for classifying and identifying the LOS or NLOS channel environment in which the device is located; and a hybrid positioning module for dynamically selecting a base station ranging method or GPS positioning technology for positioning according to the classification and identification results of the channel environment classification module. The random forest algorithm is used to classify and identify the channel environment, so that the system can dynamically select a base station ranging method or GPS positioning technology to adapt to the LOS or NLOS channel environment in which the device is located, which solves the limitations of traditional positioning methods in complex environments, improves the accuracy of device positioning, and reduces the energy consumption of the device.

The invention discloses a metasurface-assisted multi-channel super-resolution DOA (direction of arrival) estimation method based on off-grid sparse Bayesian learning. The implementation mode of the method is as follows: giving an incoming wave signal, and establishing a signal model for the incoming wave signal to reach a metasurface array element; according to the transmission amplitude and the transmission phase of the transmission type metasurface, establishing a signal model of an incoming wave signal transmitting out of the metasurface; establishing a signal model of a receiving end of the receiving antenna according to the position relationship between the receiving antenna and the metasurface; grid division is carried out on the airspace, and a sparse flow pattern array is constructed; according to a Bayesian learning algorithm, carrying out hyper-parameter initialization by utilizing the collected signal sample value, and carrying out iteration on hyper-parameters according to the idea of an expectation maximization algorithm; and finally, constructing a power spectrum function, and visualizing a calculation result to obtain a direction of arrival estimation result. Compared with an existing DOA estimation method, the method has better estimation performance and higher resolution under the condition that the number of receiving channels is the same. According to the invention, high-precision target estimation and super-resolution capability are guaranteed, the number of receiving channels is reduced, the complexity of a receiving system is reduced, and the system cost is saved.

A method comprises: by a DF antenna array, receiving a modulated RF signal and converting the modulated RF signal to multiple modulated RF channels; converting the multiple modulated RF channels to multiple channels of in-phase (I) and quadrature (Q) (I / Q) data; by a side-channel antenna, converting the modulated RF signal to a modulated RF side-channel; converting the modulated RF side-channel to a side-channel of I / Q data; demodulating and decoding the side-channel of the I / Q data to yield demodulated data; remodulating the demodulated data to produce remodulated reference I / Q data; correlating the remodulated reference I / Q data against the multiple channels of the I / Q data to produce correlation results for the multiple channels of the I / Q data; and determining an angle-of-arrival of the modulated RF signal to the DF antenna array based on the correlation results.

The invention provides a two-dimensional direction of arrival estimation method under impulse noise, and the method comprises the steps: obtaining a first output matrix outputted by an augmented co-prime array and a second output matrix outputted by an augmented expanded co-prime array through a preset receiving model; the preset receiving model comprises a parallel line structure composed of an augmented co-prime array and an augmented expanded co-prime array, conjugate operation is carried out on ECA, the non-circular characteristic of signals is fully utilized, meanwhile, in order to suppress impulse noise, a correlation entropy method based on a generalized dustpan function (GVF) is utilized, and the non-circular characteristic of the signals is fully utilized. Compared with a traditional method, the method has better robustness.

A method, a sensor system, and a non-transitory computer readable medium are provided. Embodiments comprise receiving a plurality of incident signals reflected from a target at a plurality of receiver antennas. A processor identifies a subset of receiver antennas from the plurality of receiver antennas and performs angle of arrival (AOA) processing on respective incident signals of the subset of receiver antennas. The processor determines an angle of arrival of the target based on the AOA processing.

The invention relates to a method for determining the arrival direction of signal paths on an array (2) of N sensors (3), comprising a first estimation, by sparse goniometry, of the vector γ satisfying the equation: where σ2 is the noise level, Rx is the vectorized covariance matrix of the signal x(t) considered at the output of the sensor array, and B is the calibration table of the array, and a deduction of the arrival directions of the paths based on this first estimation; then a second estimation of the vector γ satisfying with with composed of crossed terms, for arrival directions defined as a function of the deduced arrival directions, a second estimation of the arrival directions of the paths as a function of this second estimation of the vector γ. Figure for the abstract: Fig. 1

A method for determining an angle of arrival at a first communication device having a first antenna and a second antenna aligned along a direction and defining a normal thereto. The method comprises performing a respective signal exchange through each of a plurality of channels between the first communication device and a second communication device, storing a first plurality of in-phase and quadrature (I / Q) samples; estimating channel frequency responses for the first antenna and the second antenna respectively; measuring a respective distance; creating respective standard channel frequency response components corresponding to the respective distances; for each propagation path, selecting a first respective weight and a second respective weight; selecting a weight w1(1) and an other weight w2(1);determining, based on the weight w1(1) and the other weight w2(1), the angle of arrival, relative to the normal, of signals direct from the second communication device.

A ground antenna determines the current time and its own location from received signals transmitted by communication artificial Earth satellites. A high-gain, multi-beam, electrically steered antenna, combined with a processing system, measures the angle between two or more satellites and determines the current distance to each satellite through information broadcast on the TT&C channel. Knowledge of the angle and distance, along with the satellites' trajectories, can be combined with their locations predicted by satellite ephemeris data to triangulate the receiver's location. This system differs from traditional GPS antennas because it does not require coordinated active communication with the satellites to derive a location estimate. Location is calculated by the ground terminal, not the satellite. This system can be used when other location services are offline, jammed, or otherwise unavailable to maintain location and time synchronization.

Receiving device for receiving radio waves transmitted by a transmitter and for estimating the angle of incidence of a direct wave from the transmitter, comprising: first to Nth (where N is an integer not less than 2) wireless receiving devices, each provided corresponding to first to Nth antenna elements forming a group antenna, and performing frequency conversion and A / D conversion on first to Nth analog signals obtained by receiving the radio waves each through the first to Nth antenna elements to output first to Nth digital signals; First to Nth transmission channel estimation units for estimating transmission channel frequency characteristics based on the first to Nth digital signals, and outputting first to Nth transmission channel estimation results; a delay time estimation unit for estimating, by means of a super-resolution process, delay times of one or more arriving waves contained in the radio waves, based on a transmission channel estimation result within the first to Nth transmission channel estimation results; a delay time grouping unit for comparing the delay times estimated by the delay time estimation unit with a threshold to determine whether the estimated delay times are shorter than the threshold; first to Nth delayed wave removal units, each corresponding to the first to Nth transmission channel estimation units, which remove an incoming wave component from the first to Nth transmission channel estimation results according to the delay time determined by the delay time grouping unit to be equal to or greater than the threshold, and output the first to Nth transmission channel frequency characteristics with respect to the incoming waves of the delay times determined by the delay time grouping unit to be shorter than the threshold; first to Nth incoming wave separation units, each provided corresponding to the first to Nth delayed wave removal units, and each separating incoming wave components contained in the first to Nth transmission channel frequency characteristics from each other to extract first to Nth direct wave components; and an incidence angle estimation unit for estimating an incidence angle of the direct wave based on a phase difference between the first to Nth direct wave components.

The present invention discloses a method for measuring the height of a meter-wave MIMO radar under complex terrain conditions. Aiming at the problem of measuring the height of a meter-wave MIMO radar system under an actual complex position environment, a signal model that considers factors such as multiple reflection points, ground undulations, and ground reflective media is proposed. For the signal model, a generalized MUSIC or maximum likelihood estimation algorithm is used to calculate the target elevation angle. The signal model established in the present invention is closer to the actual terrain and more refined, and the method can estimate the target elevation angle and height parameters without any prior information such as known reflection coefficients and wave path differences. The studied height measurement method is less affected by complex terrain and has good position adaptability and robustness.

A radar system (1) for detecting occupied frequency channels is proposed, comprising N receiving channels (20n) capable of receiving each of the signals (Srn). For each channel (20n), the system includes a conversion unit (22n) in the spectral domain of said received signals (Srn) to form a converted signal (Sn) on an instantaneous frequency band associated with frequency channels (F), a correlation value determination module (24n) (Rn(F)) applying a power correlation between the spectrum of the converted signal (Sn) and the spectrum of an arbitrary reference signal chosen from one of the converted signals propagated on one of said channels, and an evaluation module (30) determining the sum channel values ​​from the correlation values ​​(Rn(F)). The frequency channel (F) is considered occupied if the value of the associated sum channel is greater than a predefined detection threshold value. [Fig. 1]

A ground antenna determines the current time and its own position from received signals that were transmitted by artificial earth satellites for communication. A high-gain multi-beam electrically-steered antenna is combined with a processing system to measure the angles between two or more satellites and determine the present distance to each satellite by the information broadcast on the TT&C channel. The knowledge of the angles and distances, as well as the trajectory of the satellites, can be combined with their locations as predicted by the satellite ephemeris data to triangulate the location of the receiver. This system is different from conventional GPS antennas because it does not require the cooperation of active communication with the satellites to derive a location estimate. The location is computed by the ground terminal, not by the satellite. This system can be used in cases where other locating services are offline, jammed, or otherwise unavailable to maintain location and time synchronization.

The invention provides a short-distance friend machine link instant identification method based on a Kolmogorov-Arnold network. The method comprises the following steps: receiving an array broadband baseband signal on site and carrying out channel time alignment; performing time-frequency occupancy detection on the broadband array data, and segmenting according to a burst boundary to obtain candidate link segments; the MUSIC arrival angle is calculated for the fragment in a windowing mode, an arrival angle track is formed, the direction stability is calculated and compared with a threshold value, and direction stability gating is carried out; extracting a starting waveform shape, a short-time carrier offset and a power fluctuation rhythm in the fragment through the fragment, and splicing into a link characteristic time sequence; inputting the data into a Kolmogorov-Arnold network to generate a link representation vector, fusing direction stability in a confidence degree judgment head, and outputting a friend machine recognition result in combination with a similarity threshold value of a registered friend machine feature library; generating an avoiding frequency band and an avoiding direction range and restraining a suppression frequency band and a transmitting direction of the countering equipment; according to the method, the reliability of instant identification and avoidance configuration of the friend machine link can be improved.

The present disclosure provides a multi-target position classification wireless sensing method. The method comprises: determining a channel impulse response of a received sensing signal of each antenna element in a multi-antenna array; according to the channel impulse response of the received sensing signal on each antenna element, calculating an angle of delay / angle of arrival (AoD / AoA) spectrum; according to the AoD / AoA spectrum, dividing and classifying a path distribution area; when the path distribution area contains a separable path, taking as the angle of arrival of the separable path an angle corresponding to the maximum amplitude point in the fuzzy range of the separable path, and taking as the time of arrival a time corresponding to the maximum amplitude point in the fuzzy range; and when the path distribution area contains a non-separable path, then according to an angle fuzzy range and a time delay fuzzy range of a graph comprising the non-separable path, estimating the angle of arrival and the time of arrival of each non-separable path in the non-separable-path graph. The present disclosure further provides an electronic device and a computer readable medium.

The application discloses an ultra-resolution coprime planar array spatial spectrum estimation method based on optimal structured virtual domain tensor filling, mainly solves the problem that patch missing elements in a virtual domain tensor are difficult to be effectively filled and spatial spectrum resolution performance is limited, and the implementation steps are as follows: tensor signal modeling of a coprime planar array; derivation of an augmented virtual planar array based on inter-correlation tensor dimension merging; construction of a virtual domain tensor based on mirror expansion of a non-continuous virtual planar array; virtual domain sub-tensor superposition transformation reconstruction of the virtual domain tensor; optimal structured virtual domain tensor optimization based on virtual domain sub-tensor dimensions; structured virtual domain tensor filling based on an alternating direction multiplier method; and ultra-resolution spatial spectrum estimation by decomposing the filled structured virtual domain tensor. The application realizes optimal filling of a coprime planar array virtual domain tensor, fully utilizes all non-continuous virtual domain statistical information of the coprime planar array for ultra-resolution spatial spectrum estimation, and can be used for target positioning.