108 results about "Radio map" patented technology

Embodiments described herein provide a system, method and computer program for dynamic radio map generation, which may be used for indoor positioning of one or more mobile devices based on received signal strength (RSS) in some examples. In an aspect, a dynamic scheme may be used to learn the RSS radio map from only a small number of fingerprint samples. Compressive sensing may be applied to build the graph structure and calculate the graph weight in some embodiments. Once the RSS radio map is learned, a mobile device may be located and location based services can be provided to the user in some example embodiments. An indoor learning and positioning system on a mobile device may be used to evaluate the performance. Embodiments described herein may not require a large amount of offline calibrations, which may reduce the labor cost of collecting fingerprints significantly while maintaining a satisfactory level of localization accuracy.

The present invention provides a system, method and computer program for anonymous localization. The location of a mobile device can be determined based on received signal strength (RSS) from one or more access points (APs) and a radio map. A radio map can be generated by measuring RSS at a set of fingerprints, which are a finite set of reference points within the area to be mapped.

In a wireless communication network, the location of an addressable receiver relative to the locations of a plurality of addressable sources of electromagnetic radiation is found using probabilistic models of the signal strength measured at the addressable receiver. The inventive method provides location determination on a finer spatial scale than was heretofore available. A region of interest is calibrated via a discrete-space radio map storing probability distributions of received signal strength at the measurement locations. The stored probability distributions are compensated for temporal variability and biases, such as through temporal correlations of the sampled received signal strength. A measurement of the signal strength at the addressable receiver from each of the plurality of addressable sources is used in conjunction with the discrete-space radio map to identify one of the coordinates thereof that maximizes the conditional probability P(x|s), where x is the radio map location and s is a vector of measured signal strengths. Small spatial scale variability can be compensated for using a perturbation technique. The method further implements a continuous-space estimator to return an estimated user location that falls between discrete-space radio map locations.

Systems, devices, methods, and computer-readable mediums for generating a radio map of an area are disclosed. In one aspect, the device, method, and computer-readable medium perform processes that may include receiving in at least one processor first information associated with at least one wireless device at a first location in the area. The processes may include receiving in the at least one processor second information associated with at least one wireless device at a second location in the area and different from the first location. The first location within said area and the second location within the area are unknown to the at least one processor. The processes may also include generating a radio map of the area using the first information and the second information.

The present invention provides a new and unique method and apparatus for providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network, the estimate being based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map. The signal strength database or radio map is built using a signal strength fingerprint algorithm. The signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

The present invention provides a new and unique method and apparatus for providing an estimate of a mobile location of a wireless node, point or terminal in a wireless local area network (WLAN) or other suitable network, the estimate being based on a correlation of a radio frequency (RF) signal strength measurement and a grid point in a signal strength database or radio map. The signal strength database or radio map is built using a signal strength fingerprint algorithm. The signal strength fingerprint algorithm includes selecting and measuring a set of grid points in the wireless local area network (WLAN) or other suitable network.

A drone control apparatus and method are disclosed. The drone control apparatus according to an exemplary embodiment of the present disclosure includes a communication unit that communicates with a drone operation system and a drone over a wireless communication network, a storage unit that stores radio wave environment information of the wireless communication network according to a spatial position, and flight restriction information, and a determination unit that determines a flight path and a flight altitude of the drone based on a radio map, the flight restriction information, and a departure and a destination of the drone received from the drone operation system, and transmits the flight path and the flight altitude to at least one of the drone and the drone operation system via the communication unit.

A method and system of generating an indoor radio map. In order to reduce the influence of multipath effect on indoor localization and improve the accuracy of indoor localization, a technique of processing data for indoor target locating and a technique of locating an indoor target based on the above technique is proposed. The method for generating an indoor radio map performs a smoothing process on the wireless signal strength measured in at least one position by a mobile node based on wireless signal strengths measured by the mobile node at adjacent positions, so as to reduce the influence of multipath effect.

The invention discloses a WiFi indoor positioning method of semi-supervised manifold learning based on category matching, and relates to an indoor positioning method. The WiFi indoor positioning method disclosed by the invention is used for solving the problems that a Radio Map database is large and the like in an existing WiFi indoor positioning method. The WiFi indoor positioning method comprises the following steps: 1. collecting Radio Map; 2. carrying out intrinsic dimension analysis on the Radio Map; 3. carrying out clustering analysis on the Radio Map; 4. carrying out dimensionality reduction on the Radio Map; 5. adding RSS in the Radio Map to obtain Radio Mapul; and 6. carrying out dimensionality reduction on the Radio Mapul to obtain a characteristic transformation matrix V, and forming an online positioning database through the Radio Map * and V. The WiFi indoor positioning method also comprises the following steps: 1. online testing RSS; 2. carrying out dimensionality reduction on the RSS to obtain RSS *; 3. outputting a positioning result; and 4. updating the database. The WiFi indoor positioning method disclosed by the invention is applied to the field of network technology.

The invention relates to a WIFI (Wireless Fidelity) positioning method and a positioning system thereof. The WIFI positioning method comprises the following steps of: arranging a WIFI positioning system comprising an access point, a dynamic label, a mobile unit, a center server and a database; generating each AP (access point) signal radio map of a reference system, and storing a database (DB); generating a newly-added TAG signal radio map of the reference system, and storing into the database (DB); on a mobile unit (MU), sampling each reference point signal SS of the reference system; according to the historical data of a sampling signal, carrying out iteration smooth filtering; on a center server LOC (Lines of Communication), obtaining the signal radio map of each reference system of the collected signal; according to an optimal algorithm, obtaining the geometric position of the sampling point; on the mobile unit (MU), finishing Kalman filtering to a moving object; and at the idle time of the center server LOC, finishing evaluating and updating the TAG position. According to the WIFI positioning method, the positioning precision of the whole positioning system can be improved so as to consider the data transmission efficiency and reliable positioning. The WIFI positioning method can be widely applied to the wireless positioning field.

The invention discloses a Bayes Regression-based Radio Map correction method in WiFi (wireless fidelity) indoor location. The method comprises the following steps of A, performing a location request: WiFi equipment sends a location request, searches a power fingerprint and sends to a location server; B, performing position estimation: the location server compares the current power fingerprint with the power stored in the Radio Map, and gives the current WiFi power fingerprint value to predict the position of the current node; C, performing precision adjustment: performing online dynamic correction on the Radio Map by using a Bayes Regression algorithm, reducing a power standard value to the precision of the meter level by Gaussian process regression and iteration and converting to the standard difference of the position error; D, performing location reply: the location server sends the standard difference of the prediction position and the position error to a location requesting party by a WiFi network. According to the method, the hardware investment and location delay are reduced, and a more reliable prediction result is provided for the location object.

A method is described for expanding the radio-map of a WiFi system. A hotspot (HS4) of which the position is unknown and to be estimated is “seen” in a number of fingerprints (FP1, FP2, FP3), each taken at a different position. Several hotspots with a known position (HS1, HS2 and HS3) are also “seen” in the fingerprints (FP1, FP2, FP3). The geo-positions of the measurement locations, where the fingerprints (FP1, FP2, FP3) were taken, are estimated based on the signals from the hotspots (HS1, HS2, HS3) with known geo-position seen in the fingerprints and the known geo-positions of those hotspots. The position of the hotspot (HS4) is determined based on the signals from that hotspot (HS4) seen in the fingerprints and the geo-positions of the measurement locations where the fingerprints were taken, estimated in the previous step.

The invention discloses an indoor fingerprint positioning improvement method based on area division and a network topology and belongs to the communication technology field. The method comprises the following steps of S1 determining a sampling layout and a system coordinate system; S2 on a off-line acquisition phase, collecting and receiving a signal intensity indication RSSI value at each sampling point; S3 storing the RSSI value at an acquisition point, a MAC address and a coordinate at the acquisition point, and constructing a Radio Map database; S4 collecting the RSSI value at a position to be positioned, and matching a collected signal intensity value and a signal intensity value in the database; and S5 taking a fingerprint which is matched successfully as a position coordinate of a point to be measured. In the method, an area division strategy and a network topology structure are used to construct a network, fingerprint database information accuracy and on-line matching precision are increased, positioning is stable, and the positioning is performed and simultaneously network system stability is enhanced.

The present invention provides a pedestrian location method in an indoor WLAN environment. The pedestrian location method in the indoor WLAN environment takes the Hidden Markov Model of the pedestrian mobile location as the basis, utilizes the fuzzy thinking, employs the reconstructed radio map and a planning path to estimate a Hidden Markov Model transfer matrix through the RSSI changing index fuzzy matching and finally employs the Hidden Markov Model transfer matrix to match the RSSI changing index obtained at the real location to estimate the user position so as to realize the location in the pedestrian mobile process. The fuzzy matching algorithm estimates the pedestrian position through the proportional relation of the wireless network signal fading and the distance, the fuzzy matching algorithm can be also individually used for pedestrian mobile location, and because of the iterative computations character, big location errors are likely to be introduced so as to introduce the Hidden Markov Model in the present invention. The pedestrian location method in the indoor WLAN environment can greatly improve the location precision when the pedestrian is moved in the indoor environment and has good environment adaptability and anti-interference performance.

The invention discloses a building indoor floor plan establishment method based on a laser ranging sensor, and relates to the technical field of indoor positioning. By means of the building indoor floor plan establishment method based on the laser ranging sensor, trajectory tracking of an indoor moving object can be achieved, and the problem that an indoor map is lacked in the process of rapidly establishing Radio Map in the field of indoor positioning is solved. The building indoor floor plan establishment method based on the laser ranging sensor is characterized in that building indoor laser measurement data are obtained; laser measurement data images are spliced, the rotation matrix and the translation matrix of two adjacent sets of the laser measurement data are obtained, the laser measurement data are converted to a point set within a former coordinate system by means of the obtained corresponding rotation matrix and translation matrix, forward iteration is continuously conducted, and splicing of the laser measurement data images is completed; geometric correction of errors, deletion of redundant data and filtering removing of noise points are sequentially conducted on the spliced images. According to the building indoor floor plan establishment method based on the laser ranging sensor, in the process of rapidly establishing the Radio Map in the indoor environment, the requirement of a user for rapidly establishing an indoor two-dimensional map is met, and meanwhile trajectory tracking of indoor moving objects can be achieved.

A method and apparatus for determining location information of a position in a multi-storey building, the method comprising: retrieving observation data comprising observed addresses and corresponding observed received signal strengths of wireless access points detected at the position from a memory; retrieving, for each storey of the building, a radio map comprising a plurality of location points in the respective storey of the building from a database; selecting one or more location points comprising the observed addresses from the radio map; determining a storey estimate of the position by calculating a sum probability for each storey of the building; and setting the storey estimate as the storey of the building having highest value of the calculated sum probability.

A method of positioning using wireless signals and an inertial measurement unit is provided. The method includes the following steps: providing a wireless signal strength data base, wherein the wireless signal strength database gathers a radio map and a plurality of wireless signal strength information corresponding to a plurality of orientations at all grid positions on the radio map; using the inertial measurement unit to detect a current orientation at a current position where the electronic device is located; detecting a current wireless signal strength information of the electronic device corresponding to the current orientation at the current position; and determining the current position according to the current orientation, the current wireless signal strength information, and the wireless signal strength data base.

An apparatus for creating a radio map includes a radio signal acquiring unit that acquires information on radio signals between one or more cooperative intelligent robots, a radio environment modeling unit that estimates radio strength for each cell configuring the radio map from the information on radio signals acquired by the radio signal acquiring unit, and a radio map creating unit that classifies a communication region of each cell and models the radio map according to the radio strength for each cell estimated by the radio environment modeling unit.

The invention relates to an automobile location method, and especially an indoor parking lot location method. The method comprises the steps of 1, setting a reference node for a location scene, collecting an RSSI of the reference node, and establishing a Radio Map composed of a coordinate of the reference node and the RSSI of the reference node; 2, carrying out Euclidean distance operation by employing the RSSI collected by a terminal and the RSSI in a fingerprint library; and 3, determining the minimum reference node coordinate obtained through the Euclidean distance operation as the location of a target. According to the indoor parking lot location method provided by the invention, the environment parameters in the location scene are precise, the data collection workload is low, the calculation quantity is small, the location precision is high, and the cost is low.

The invention relates to a local linear embedded algorithm based radio frequency map unsupervised classifying method and aims at solving the problem that existing radio frequency map classifying methods can only depend on space distribution of a to-be-positioned area for classification. The method includes setting an access reference point and a test point in a to-be-positioned indoor area; determining a matrix of a Radio map according to the position of the test point and RSS (radio-frequency signal strength) of the access reference point; processing data of the Radio map, namely, storing space coordinate information in the Radio map into storage equipment, and deleting the space coordinate information to acquire actual high-dimension data X=(x1, x2, ..., xt); and building a local covariance matrix Q according to adjacent points, calculating low-dimension embedding by utilizing a local reconstruction weigh matrix W, dividing low-dimension data into S classes and judging inter-class divergence and in-class divergence, merging the classes according to ratio conditions, and acquiring a final class information matrix. The local linear embedded algorithm based radio frequency map unsupervised classifying method can be widely applied to unsupervised classification of radio frequency maps.

The invention provides a method for WLAN indoor positioning Radio Map updating based on information entropy and relates to a WLAN indoor positioning method. The method solves the problem that an existing WLAN indoor positioning Radio Map updating method is poor in positioning accuracy, has complexity in positioning and is large in updating workload. AP signal strength RSS values measured in every reference point are stored in a Radio Map, APs with information entropy large are selected, mutual information entropy between every two APs is calculated; after the APs with information entropy large are selected, a Hidden Markov model is utilized to update the Radio Map at an off-line stage, a KNN algorithm is used to respectively compare positioning accuracy of the Radio Map at the off-line stage and the updated Radio Map with RSS vectors measured at an on-line stage, and the updated Radio Map is favorable for improving positioning accuracy compared with the Radio Map prior to updating. The method is suitable for WLAN indoor positioning.

The present invention is related to method and device for building Wi-Fi radio map. Especially, it is related to device and method for building Wi-Fi radio map that is used to position locating service that utilizes Wi-Fi fingerprints that many, unspecified mobile terminals collect and provide. Specifically, the present invention provides, as methods for estimating position data for AP (200) using Wi-Fi fingerprints collected by mobile terminals (100), 1) method for estimating position data for AP (200) by linking Wi-Fi fingerprints and time data for collecting Wi-Fi signal, or 2) method for estimating position data for AP (200) through user address data comparison between Wi-Fi fingerprints without linking signal collection time data to Wi-Fi fingerprints. Accordingly, it has effects of epoch-making economic feasibility compared to prior art that requires huge cost in collecting Wi-Fi fingerprint like war driving.

The invention discloses a satellite-ground interference coordination method, device and equipment based on radio map information. The method is suitable for a spectrum sharing scene of a satellite communication system and a distributed antenna communication system, and comprises the following steps of acquiring radio map information in the frequency spectrum sharing scene; utilizing the radio mapinformation to solve a maximum average sum rate of the distributed antenna communication system according to a wireless channel model; obtaining sending power sent to each wireless user terminal by each base station antenna unit in the distributed antenna communication system according to the maximum average sum rate of the distributed antenna communication system; and adjusting power transmittedto the wireless user terminal by each base station antenna unit in the distributed antenna communication system according to the obtained sending power. According to the method, the device and the equipment, efficient frequency spectrum sharing of the satellite communication system and the distributed antenna communication system can be realized, so that the range of shared frequency bands of thesatellite communication system and the distributed antenna communication system is expanded.

The invention relates to a WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method, in particular, a linear regression algorithm-based WLAN indoor positioning multi-user RSS fusion method. The objective of the invention is to solve the problem of large positioning errors caused by large difference of RSS data acquired by users through using different mobile terminals in a radio map building process and an online positioning stage. According to the method of the invention, in an off-line stage, linear regression processing is performed on RSS values acquired by the different mobile terminals, and at the same time, the linear regression coefficients of the different mobile terminals and a base mobile terminal are stored; in an online positioning stage, a system obtains the brands of the mobile terminals of the users, and reads the linear regression coefficients from a radio map so as to perform linear regression processing on the RSS values acquired by the mobile terminals; and therefore, the differences between the RSS values which are acquired online and the RSS values in the radio map caused by the differences of devices can be eliminated, and online positioning accuracy can be improved.