20 results about "Multilateration" patented technology

A computer-implemented method for establishing and controlling a mobile perimeter and for determining a geographic location of an RF emitting source at or within the mobile perimeter includes receiving from RF sensors in a network, processed RF emissions from the source collected at RF sensors. The RF emissions follow a wireless protocol and include frames encoding RF emitting source identification information. The method further includes extracting RF emitting source identification information from the frames, processing the source identification information to identify the RF emitting source, and classifying the RF emitting source by one or more of UAS type, UAS capabilities, and UAS model. The method also includes receiving from the RF sensors, a geographic location of each RF sensor and a time of arrival (TOA) of the RF emissions at the RF sensor; and executing a multilateration process to estimate a geographic location of the RF emitting source.

The invention relates to an ultrasonic measuring unit (1), in particular for use in a vehicle (2), comprising a control unit (3) and an evaluation unit (4), wherein the control unit (3) is designed to control first ultrasonic transducers (11) for transmitting ultrasonic signals and, on the basis of reception signals generated with the aid of second ultrasonic transducers (12), to detect echoes produced owing to signal paths of the ultrasonic signals, and the evaluation unit (4) has a trained AI module (5) and is designed to process the reception signals in order to detect an object (6; 60) causing the echoes, wherein the processing involves at least generating feature vectors (111, 112, 113) on the basis of the reception signals with the aid of the AI module (5), and the control unit (3) or the evaluation unit (4) is configured to determine, on the basis of the reception signals, a signal propagation time or signal propagation distance corresponding to the signal path for the associated echo, and the AI module (5) is designed to determine the feature vectors (111, 112, 113) on the basis of the signal propagation times or the signal propagation distances.

The application discloses a dynamic combination station site optimization method and device of an air traffic control multilateration system, and the method comprises the following steps: a station dynamic weight evaluation model is established to determine station weights; a geometric precision factor lookup table is established to be used for dynamically extracting a station combination geometric precision factor; and an adaptive combination optimization algorithm is used to determine an optimal station combination. Through a dynamic station optimization mechanism, the method can real-timely evaluate station signal quality, geometric distribution and redundancy, adaptively adjust a station combination participating in positioning, and improve robustness in a complex scene. In addition, the method also adopts a multi-target optimization model based on dynamic weights, combines parameters such as signal arrival time difference error, geometric precision factor and calculation resource consumption, realizes rapid screening of an optimal station combination, effectively reduces calculation load, and guarantees positioning reliability.

The invention discloses a device and method for transmitting multi-point GNSS positioning signals in an indoor distribution system, and relates to the technical field of indoor distribution systems and satellite positioning, the device is adaptive to the tree topology indoor distribution system, and comprises a GNSS signal simulation unit, a frequency generation unit, a combination transmission unit, a terminal processing unit and a positioning broadcast unit; the simulation unit generates GNSS positioning signals GPn of different virtual positioning points through at least two simulators, the frequency generation unit generates local oscillation signals LIN through frequency generators in one-to-one correspondence and performs frequency conversion with the GPn, and the combination transmission unit combines the frequency conversion GNSS signals and the LIN and then broadcasts the frequency conversion GNSS signals and the LIN in a unified manner through POI and indoor distribution feeder lines. The tail end processing unit screens matched signals through a conditioning circuit and recovers GNSS navigation signals of correct frequency points, and the positioning broadcasting unit broadcasts the navigation signals through a newly-added antenna. On the basis of the device, multi-point GNSS positioning signal transmission and broadcasting under the feeder non-power-supply condition are achieved, the problem that a traditional indoor distribution system is difficult to integrate the positioning function is solved, and indoor precise positioning is achieved.

Airfield surveillance unit (11) for detecting airfield traffic and airfield multilateration system comprising such airfield surveillance unit. The airfield surveillance unit comprises a power supply module (113), a first radio antenna (111) configured to receive an aircraft transponder signal, a receiver module (112) coupled to the power supply module (113) and to the first radio antenna (111) and comprising a first data communication port (1122, 1123). The receiver module (112) is operable to convert the aircraft transponder signal received by the first radio antenna (111) to a multilateration-purpose signal for transmission via the first data communication port. The airfield surveillance unit further comprises a second radio antenna (118) and a 5G communication module (117) coupled to the power supply module (113) and configured to be coupled to the second radio antenna for operating as a transceiver for a mission critical private 5G cellular network.

A communication system may include a transmitting (TX) device, a receiving (RX) device, and a one or more reconfigurable intelligent surfaces (RIS's). The TX device may transmit a wireless signal received by the RX device over multiple propagation paths including paths that reflect off the RIS(s) and paths that include other reflections. The RX device may receive location information from each RIS. The RX device or a control device may control each RIS to modulate the wireless signal with a different respective identifier upon reflection of the wireless signal by the RIS. The RX device may distinguish the wireless signal as reflected off the RIS(s) from reflections off other objects based on the RIS identifiers modulated onto the wireless signals by the RIS(s). The RX device may use a multilateration technique to detect its position based on the received location information and the wireless signals as reflected off the RIS(s).

The application discloses a kind of low-altitude unmanned aerial vehicle autonomous flight path control method in transformer substation, it is related to the technical field of power system automation inspection, comprising: obtaining the real-time spatial coordinate system constructed by at least three transformer substation positioning devices, carry out fusion operation with the three-dimensional coordinate system of transformer substation established in advance, obtain the flight coordinate data of unmanned aerial vehicle;Unmanned aerial vehicle flight node is generated based on flight coordinate data, and the connection between flight nodes is determined according to preset path planning rules;In the process that unmanned aerial vehicle flies according to flight node, unmanned aerial vehicle position data is collected according to preset frequency, when unmanned aerial vehicle reaches preset flight node, spatial position measurement and correction are carried out, and abnormal data is filtered according to preset rules.The application improves the inspection efficiency and safety of unmanned aerial vehicle in transformer substation by multi-point positioning, real-time data updating, position correction, optimized path planning and multi-level data filtering mechanism.

The invention discloses an anti-interference method and device based on a multi-point positioning system, and the method comprises the steps: receiving the pixel data of a frame image, comparing the pixel data of a current frame image with the cached pixel data of a previous frame image, judging whether the pixel of the current frame image is brightened or not, and if the pixel of the current frame image is brightened, judging whether the pixel of the current frame image is brightened; marking that the pixels of the current frame image are brightened and storing the pixels of the current frame image into a cache; comparing the pixel data of the frame image after the current light-emitting device is turned off with the pixel of the previous frame image in the current cache; if the pixels of the frame image after the current light-emitting device is turned off are darkened, continuing to judge whether the pixels of the darkened frame image after the current light-emitting device is turned off mark to be brightened or not; and determining the pixels of the frame image marked to be brightened and darkened after the current light-emitting device is turned off as bright spot pixels, storing the current bright spot pixels in a cache, and counting and outputting bright spot coordinates of the bright spot pixels. According to the invention, the interference of ambient light can be effectively eliminated; the light spot positioning precision is improved, and positioning failure is effectively avoided.

A method and system for enabling the determination of a position of a receiver within a space includes transmitting a beacon signal from each of a plurality of beacon devices located at different locations within the space. The beacon signal transmitted from each beacon device has a unique information component and may have a unique frequency pattern of multiple frequencies. Each beacon signal can be distinguishable from the beacon signals transmitted from any other of the beacon devices based on the combination of its unique information component and its unique frequency pattern. The beacon signals are received at a receiver. At the receiver, for each beacon signal of a working subset, time-delay information of the received beacon signal is determined and multilateration is applied to determine the position of the receiver based on the location of each beacon device of the working subset.

The invention relates to a method (100) for determining an uncertainty of the position of a target object (20), comprising the following steps, which are carried out by an entity (10): - Receive (101) one or more arrival time measurements carried out by at least one anchor device (30, 31, 32) to a target object (20), - Requesting (102) an absolute position from each of the at least one anchor device (30, 31, 32), - Performing (103) a multilateration based on the one or more arrival time measurements and based on a closed-form procedure to obtain an absolute position of the target object (20), - Calculating (104) a Jacobian matrix J based on a multilateration model with respect to the absolute position of the at least one anchor device (30, 31, 32) and with respect to the one or more arrival time measurements, - Compiling (105) a variance and / or covariance matrix of the respective absolute positions and the one or more arrival time measurements based on the Jacobi matrix J to calculate the absolute position of the target object (20), - Calculating (106) a variance and / or covariance matrix of the absolute position of the target object (20), - Determining (107) the uncertainty of the absolute position of the target object (20) based on the calculation (106). Furthermore, the invention relates to a computer program and a data processing device for this purpose.

This application relates to a multi-station, multi-target matching algorithm and system for OFDM sensory integration system that integrates radial velocity. The method includes constructing sensor node groups among all sensor nodes; determining a set of candidate locked targets for each sensor node group; filtering sensor node groups belonging to the same candidate locked target to obtain a tracking node group; converting candidate locked targets matched with the tracking node group into locked targets; completing the pairing relationship between the remaining sensor nodes and locked targets; if candidate locked targets still exist, continuing to construct sensor node groups and perform matching until the candidate locked targets disappear; and relocating the locked targets using distance measurement information from all sensor nodes. The multi-station, multi-target matching algorithm and system for OFDM sensory integration system that integrates radial velocity, based on multi-point positioning and simultaneously introducing a multi-dimensional judgment method, achieves early elimination of infeasible associations, significantly improving association reliability while ensuring positioning accuracy.

This invention discloses a dual-antenna positioning method based on the spatiotemporally inseparable characteristics of electromagnetic flying rings, belonging to the field of spatiotemporally inseparable electromagnetic pulse technology. The method first utilizes two electromagnetic flying ring generator antennas located at different spatial positions to emit two electromagnetic flying rings in a three-dimensional space. Then, the arrival time, spectrum, and polarization of the electromagnetic flying rings at different spatial positions are measured, and the measurement data is stored to establish a spatial location information database. Subsequently, the arrival time, spectrum, and polarization at the target location are measured, and the data are compared with the information in the database to calculate parameters such as the degree of temporal entanglement, thus obtaining the three-dimensional spatial coordinates of the target location. This invention provides ideas and methods for simplifying existing multi-point positioning techniques and developing new electromagnetic pulse applications, and has significant research value.

The invention provides a mobile communication device and a searching and rescuing system thereof, and the mobile communication device is provided with a rescuing application program which can enter energy-saving operation and send a rescuing signal containing position information in a preset period when a disaster prevention alarm is triggered or a user manually starts the mobile communication device. The plurality of unmanned vehicles carry a signal receiving module, a network module and an edge operation module so as to receive rescue signals, obtain position information and carry out initial position estimation. A multi-node wireless network can be formed among the unmanned carriers, and multi-point positioning information can be generated. The rescue platform integrates the positioning data from the unmanned vehicle, and uses a positioning algorithm to calculate and generate rescue positioning information so as to assist in determining the position of the mobile communication device. Besides, the unmanned vehicle can perform regional search formation, and is provided with an electric energy transmission module to supplement electric power for the mobile communication device in a long distance, so that the mobile communication device can restart a rescue application program and continuously send a rescue signal, and the disaster search and rescue efficiency is improved.

The application discloses a data interpolation prediction method based on a multilateration system, acquires different target message data, and interpolates one kind of message data to another kind of message data, so that asynchronization between different message data is reduced, and the problems of large positioning precision analysis error and complex method in the existing multilateration system are solved.

The invention provides a method for constructing an interactive prediction model for ground sliding tracks of multiple aircrafts. According to the model, a dynamic interaction diagram is constructed with aircrafts as nodes and spatial proximity relations as edges, historical trajectory and planned path features are extracted by adopting a Transform encoder, and dynamic influences of adjacent aircrafts on target individual trajectory evolution are aggregated through a residual multi-head GAT module. And finally, generating a final prediction track by adopting a gating fusion mechanism and a time sequence decoder, emphatically optimizing the long-term prediction precision through a weighted loss function, and performing simulation on a real airport multi-point positioning system data set. The result shows that the average displacement error and the final displacement error of the model in a multi-aircraft scene are 3.517 m and 4.082 m respectively, and the performance is obviously superior to that of a baseline model such as STGAT. According to the method, the interaction among multiple subjects can be effectively captured, and reliable support is provided for improving the scene situation real-time perception and conflict early warning capability.

Methods and media for enabling RTT-based positioning are provided. The method includes receiving, by a cloud-based location platform maintaining a beacon database, observations from a plurality of UEs that have observed beacons, the observations including at least a determined location of each UE and RTT measurements of each UE by the beacons; determining, by the cloud-based location platform, the physical antenna location of the beacon based at least on the determined location of each UE and the RTT measurement of each UE using a WLS multilateral measurement algorithm in which the weight is a function of the location confidence of the determined location of each of the plurality of UEs; updating the beacon database to include the determined physical antenna position of the beacon; and providing, by the cloud-based location platform, the physical antenna locations of the beacons to the one or more UEs such that the one or more UEs both contribute information to determine the physical antenna locations of the beacons to construct a beacon database and consume the physical antenna locations from the beacons in the beacon database.

Disclosed are systems, methods, and computer programs for determining a range to a target. A system can include a first receiver configured for receiving a first signal from the target and a second receiver configured for receiving a second signal from the target, the second receiver time-synchronized with the first receiver. A programmable processor can determine a range to the target based on arrival times of the first signal at the first receiver and the second signal at the second receiver.

The application discloses a kind of based on improved cuckoo algorithm's aircraft multilateration solution method, which includes obtaining multilateration mathematical model;Obtain the search area of cuckoo algorithm;Initialize population parameters;The fitness value of each bird nest is calculated, and the current optimal bird nest is recorded;The fitness value of updated bird nest is calculated and compared with the optimal bird nest fitness value;According to random preference walk, update bird nest position;Output optimal bird nest position, to obtain aircraft position and the like steps.The application utilizes Chan algorithm to process effective information, obtains initial estimated position of aircraft by twice least square estimation, reduces operation amount, and improves convergence rate of cuckoo algorithm;The initial population is chaotic in feasible region by using the thought of chaos algorithm, so that individual is relatively uniformly distributed in feasible region, and the diversity and ergodicity of initial population are strengthened;Self-adaptive discovery probability is introduced, which is conducive to balancing global exploration and local development capability of algorithm, accelerating convergence speed of algorithm, and increasing population diversity.

The invention relates to a radial velocity-fused multi-station multi-target matching algorithm and system for an OFDM (Orthogonal Frequency Division Multiplexing) sensing integrated system. The method comprises the following steps: constructing a sensing node group in all sensing nodes; determining a candidate locking target set of the sensing node group; screening the sensing node groups belonging to the same candidate locking target to obtain a tracking node group; converting the candidate locking target matched with the tracking node group into a locked target; complementing the pairing relationship between the remaining sensing nodes and the locked target; when the candidate locking target still exists, continuing to construct the sensing node group and matching until the candidate locking target disappears; and repositioning the locked target by using the distance measurement information of all the sensing nodes. According to the multi-station multi-target matching algorithm and system based on radial speed fusion of the OFDM communication and inductance integrated system disclosed by the invention, early elimination of infeasible association is realized by introducing a multi-dimensional judgment mode based on multi-point positioning, and the association reliability is remarkably improved while the positioning precision is ensured.

A system for localization of an autonomous vehicle includes a plurality of radio receivers configured to receive automatic dependent surveillance-broadcast (ADS-B) radio signals transmitted by a plurality of overhead aircraft, and at least one processor coupled to at least one memory and configured to perform operations comprising: based upon a first, a second, and a third ADS-B radio signals transmitted by a first, a second, and a third overhead aircraft, respectively, computing an angle from, and a distance between, a radio receiver to a respective overhead aircraft, and computing a relative motion of the respective overhead aircraft; and based upon position information included in the first, second, and third ADS-B radio signals, and using the first angle, second angle, third angle, first distance, second distance, third distance, the relative motion of each of the first, second, and third overhead aircraft, performing multilateration to determine a position of the autonomous vehicle.