124 results about "Centroid algorithm" patented technology

The invention provides an autonomous navigation and obstacle avoidance system and a method of an indoor mobile robot. The system comprises a wireless sensor network and a mobile robot; the wireless sensor network comprises Cricket sensor beacons, Cricket sensor receiving nodes and ultrasonic sensor nodes; indoor environment is divided into several grids; the ultrasonic sensor nodes are deployed on a ceiling according to set grids; meanwhile four or more Cricket sensor beacons are deployed randomly; an external communication module of a mobile robot master control one-chip microcomputer is connected with the Cricket receiving nodes; a segment maximum likelihood centroid algorithm is employed to locate the robot, establish a three-dimensional environment map and a grid map and construct path grids; and a global path is programmed based on an expansion algorithm and a Dijkstra algorithm. According to the invention, a sensor network with global monitoring capability is employed and introduced into indoor and dynamic environment navigation for robot, and has advantages of accurate positioning, rapid environment modeling and reasonable path programming.

The invention relates to an RSSI (Received Signal Strength Indicator) weighted centroid algorithm-based passive RFID (Radio Frequency Identification Device) label locating method, which comprises the steps of: calculating a corresponding Euclidean distance according to a to-be-located label and a signal strength value of a reference label relative to an RFID antenna, finding known reference labels of K coordinates, which are closest to the to-be-located label, wherein K is generally selected to be 4 according to the existing experiment result; calculating weights of the K reference labels which are closest to the to-be-located label; and finally, figuring out coordinates of the to-be-located label according to the coordinates and the weights of the reference labels. The method achieves a better balance between location cost and property, has the advantages of convenience, flexibility, easy configuration and the like, and can be suitable for a large quantity of RFID passive labels on the market; and because an RSSI is easy to obtain, a location system can also have better instantaneity.

The invention relates to a positioning method of weighted wireless sensor network nodes based on an RSSI and an LQI, which is characterized in that (1) the parameters of the RSSI and the LQI, which can be acquired easily from a hardware register, are used for positioning, thus the method can be realized easily and has few required hardware resources; (2) an LQI ranging model obtained by fitting experimental data is combined with an RSSI ranging model to select anchor nodes; and (3) an RSSI value and an LQI value which pass through an average filter are weighted and combined, an improved weighted centroid algorithm is used for estimating the positions of nodes to be detected, the data is broadcasted to cluster nodes, and then, the data is uploaded to a monitoring centre through a wired network. The positioning method of invention has the advantages of high positioning accuracy without being influenced by the environment easily, easy implementation of hardware, lower cost and smaller computation complexity.

The invention relates to an indoor positioning method based on a BP neural network and improved a centroid algorithm, belonging to the field of wireless communication and intelligent control. The indoor positioning method comprises the steps of: carrying out data acquisition under an indoor environment, recording and storing reference node coordinates, blind node coordinates, a distance d between a reference node and a blind node and corresponding receiving signal strength indicators (RSSI) during experimenting; training an established BP neutral network by using the RSSI and the distance d; training and checking the established BP neutral network by using an actual RSSI and the corresponding distance d to obtain a function; calling the function to obtain the distance d of the reference node and the blind node; obtaining more than three reference nodes with the distance d from the blind node; taking the three reference nodes with highest RSSI, obtaining three circles with the distance d as a radius; and solving two points of lines of centers of three circles in pairs with two points crossed with two circumferences to obtain six points, and solving centroids of the six points, i.e. the blind node coordinates. The method is more accurate in positioning, thus algorithms are simplified.

The invention relates to a method for controlling array light beam co-target collimation of a target in a loop based on light spot centroid calculation. The coordinates of the centroid of a light spot on an imaging plane are obtained through a light spot centroid algorithm, a tilt control quantity which needs to be conducted on each light beam is obtained according to the quantitative relation between tilt control of a tilting mirror of the corresponding light beam and a light spot movement vector, and the centroid of the light spot is moved to a target spot of an image device through control over the tilting mirrors. Co-target collimation of all the light beams of the target in the loop is realized through sequential control cover the array light beams. There is no need to accurately describe or obtain a light path, and a control scheme is simple and convenient and easy to implement. The adopted centroid of the light spot serves as a performance evaluation function which is simple, convenient, high in real-time performance, and remarkable in effect, and consumes a short time. The method for controlling array light beam co-target collimation of the target in the loop based on light spot centroid calculation has extensive application prospects in satellite tracking, the directed energy technology and other fields.

The invention provides a wireless sensor network search-and-rescue target location method based on maritime environment self-adaptation RSST distance measurement. Wireless sensor network application and maritime search and rescue are combined to change the situation that maritime search-and-rescue targets can only wait for rescue. A easily operated and arranged RSST distance measurement algorithm which is not required to be supported by additional hardware is selected, mobile anchor nodes are introduced based on shielding models, required parameters are calculated by utilizing mutual coordination of the anchor nodes, and optimized paths loss models can meet maritime search and rescue application environments at the moment. Gaussian filter are utilized to perform filtering on measured RSST number values, accordingly accurate RSST number values are obtained, the optimized paths loss models are substituted to obtain accurate distances between the anchor nodes ad unknown nodes. Finally, maritime search-and-rescue targets are positioned by utilizing a wireless sensor network triangular centroid algorithm, and target location accuracy and search-and-rescue success rate are improved.

The invention discloses a WSN (wireless sensor network) rapid self-positioning method based on triangle form estimation. From the aspect of triangle form estimation, a triangle centroid positioning algorithm having the minimal error is studied, and a concept of effective triangle is proposed. The triangle centroid algorithm is used on effective triangles and the error in positioning is minimal. The positioning algorithm is used on all triangles which satisfy basic conditions of effective triangle. All solved possible points are formed into a polygon. The centroid is obtained again, and an estimated position of an unknown node is obtained. Accidental calculation error is prevented by using anchor node information in a network and through a method of obtaining a mean value from multiple possible results. A method of two points positioning is introduced. In the case of only two anchor nodes, the positioning of the unknown node is realized by using an auxiliary anchor node. The positioning coverage rate of nodes is effectively improved without increasing hardware equipment and complexity.

The invention discloses a splicing detection device of a circular Hartmann-Shack wave-front sensor based on a minor caliber. The device is characterized by comprising the Hartmann-Shack wave-front sensor, an x-z 2D electric control translation stage, a step motor controller, a computer, a mirror surface to be detected and a data acquisition card; the Hartmann-Shack wave-front sensor is positioned behind the mirror surface to be detected to detect the mirror surface to be detected, and a facula lattice is formed on the Hartmann-Shack wave-front sensor, and the data acquisition card acquires the facula data and transmits the data to the computer for storing; the computer sends an instruction to the step motor controller, and controls the 2D electric control translation stage to move along an x axis and a z axis to scan and detect the mirror surface to be detected; the data acquisition card sequentially acquires the facula data of a wavelet surface of each frame, and then a wave surface to be detected is obtained by a centroid algorithm, a splicing method and a restoration algorithm. The device and the method help improve a formula by ignoring a defocus error in theoretical analysis, eliminate a principle error of a translation error, improve splicing precision and lower computation complexity of solving splicing parameters.

The invention discloses a positioning method, which comprises the following steps of: selecting four wireless nodes with known positions as reference nodes; estimating a distance from each reference node to a node to be positioned according to a signal strength value between each reference node and the node to be positioned; for a two-dimensional plane consisting of every three of the four reference nodes, obtaining the proximity position of the node to be positioned on the two-dimensional plane by using a weighted centroid algorithm according to the distance from each of the three reference node to the node to be positioned as a plane approximation point of the two-dimensional plane, wherein totally four plane approximation points are obtained; and calculating the position of the node to be positioned by using the weighted centroid algorithm again according to the obtained four plane approximation points. A positioning result obtained by the positioning method is more reliable.

The invention discloses an indoor AGV (automatic guided vehicle) navigation control method based on UWB (ultra-wide bandwidth) positioning and dead reckoning, which comprises a plurality of control steps: measurement of a distance between a single to-be-positioned node and a single reference node; measurement of distances between the to-be-positioned single node and multiple reference nodes; positioning of the to-be-positioned node; measurement of a course angle; measurement of an AGV driving distance; positioning navigation and combined positioning navigation of dead reckoning, wherein the to-be-positioned node is positioned by an inner quadrilateral centroid method, and signal flight time between the single to-be-positioned node and the multiple reference nodes is measured through a preset communicating mechanism, so as to calculate distances; finally, the positioning calculation is realized through the inner quadrilateral centroid algorithm; circles are drawn by respectively takingall the reference nodes as circle centers and taking the corresponding measured distances as radiuses; a quadrangle is formed by utilizing four close circle intersections; four vertexes of an inner quadrangle are calculated by positioning correction factors, so that estimated coordinates of the to-be-positioned node are calculated.

The invention provides a positioning method of a mobile terminal and a device thereof. The positioning method of the mobile terminal comprises the following steps of receiving broadcast signals which contain identification information and position information and are sent by each anchor node; according to intensities of the received broadcast signals, determining a distance between the mobile terminal and each anchor node to acquire a distance set; based on the distance set and position information of each anchor node, calculating a first coordinate set of the mobile terminal; according to a sequence of broadcast signal intensities from large to small, selecting the anchor nodes with a predetermined quantity to form at least one triangle or a tetrahedron, and based on a weighted centroid algorithm and the first coordinate set, calculating and acquiring a second coordinate set of the mobile terminal; according to the second coordinate set and a distance from each coordinate in the second coordinate set to a corresponding triangle or tetrahedron vertex in the at least one triangle or the tetrahedron, through the weighted centroid algorithm, calculating a coordinate position of the mobile terminal.

The invention discloses a mobile anchor node based weighted centroid locating method for a wireless sensor network node and belongs to the field of application of the wireless sensor network and the random mobile technology and the wireless range finding technology. Since a mobile anchor node is utilized to substitute for a traditional anchor node, usage cost is reduced, and coverage rate for unknown nodes is increased. Locations of the unknown nodes can be obtained by scheduling moving path of the anchor node and by the aid of the weighted centroid algorithm. The mobile anchor node based weighted centroid locating method for the wireless sensor network node is low in cost, simple in algorithm, high in coverage rate of unknown nodes, accurate in locating, and applicable to practical use.

The invention relates to a grid-clustering-based RSSI (Receive Signal Strength Indicator) indoor positioning algorithm which comprises the following steps: S1, placing an RFID (Radio Frequency Identification) fixed reader, randomly placing an active tag as a to-be-detected tag, and determining an RFID positioning system model; S2, repeatedly measuring the RSSI value from each reader to the to-be-detected tag at different moments, recording the measured value each time, and calculating the distance from the to-be-detected tag to each reader according to the acquired RSSI value; S3, acquiring aplurality of 'estimation tags' by using a trilateration algorithm, solving the mean of the coordinates of the 'estimation tags' as a 'target tag'; S4, defining a search region by taking the 'target tag' as a center, and dividing the region into grids of the same size; S5, screening the grid containing the most 'estimation tags' by utilizing a grid clustering algorithm, and selecting the 'estimation tags' in the grid as reference tags; S6, solving the centroid of the reference tags as the estimated value of the to-be-determined tag coordinate according to a weighted centroid algorithm.

The invention relates to the space technology, and to the improvement of the star sensor calibration method. The invention uses the calibration system which including air cushion platform, single-star starlight simulator, star tracker, two-dimensional axial turntable platform and data-processing computer, its steps being: establishing point spread function model, establishing a centroid algorithm formula, establishing a centroid algorithm pixel frequency error model, and data acquisition. The invention provides a more practical point spread model; improving satellite sensor calibration precision; the calibration model is simple and easy to calculate.

The present invention discloses a method for path intelligent planning of a robot cleaner. The method mainly comprises automatic positioning, path planning and road finding when encountering obstructions. The robot cleaner performs positioning through the triangle and centroid algorithm, performs bow-shaped cleaning along the longest edge of a room, performs automatic road finding along the edges when obstructions are encountered and performs traversal cleaning. The method for path intelligent planning of the robot cleaner plans the cleaning path of the robot cleaner as much as possible so as to improve the work efficiency and allow the home cleaning to become simpler and more efficient.

A method for optimizing centroid measurement precision of Hartmann wavefront sensor includes the steps of: performing threshold processing to pixel data outputted by photoelectric detector; calculating order moment centroid of each subaperture spot using the pixel data of threshold processing, wherein alpha=1, 2, 3......L; calculating repeatedly the order moment centroid of each subaperture spot; calculating the mean value of order moment centroid standard deviation of each subaperture spot; finding out the corresponding minimum order, namely finishing the method for optimizing centroid measurement precision of Hartmann wavefront sensor. Repeatedly calculating alpha order moment centroid of each subaperture spot and obtaining corresponding centroid standard deviation, thereby obtaining the excellent corresponding order which the mean value of all subaperture centroid standard deviation is small, and the filtered high-order centroid algorithm is capable of suppressing more effectively the influence of noise to centroid computational accuracy with the most excellent repeatable accuracy of centroid measurement relative to other each order moment centroid algorithm, thereby improving wavefront reconstruction accuracy.

The invention provides an indoor positioning method for RSSI ranging based on iBeacons nodes. The method comprises the following steps: S1, carrying out continuous and multiple collections of RSSI values of anchor nodes in different positions through mobile equipment in a fixed position, and establishing a corresponding relationship between the RSSI values and distances between the mobile equipment and the anchor nodes; S2, preprocessing the RSSI values, and selecting normal values from the RSSI values and establishing a corresponding relationship between the normal values and the distances to establish a ranging model; S3, collecting the RSSI values of the anchor nodes through the mobile equipment in unknown positions, and calculating the distances between the mobile equipment and all the anchor nodes through the ranging model; S4, selecting the four anchor nodes which are the nearest to the mobile equipment, and reading coordinate information of the four anchor nodes; S5, calculating the actual coordinates of the mobile equipment through the re-weighted centroid algorithm; and S6, optimizing the positioning coordinates according to map restrictions of an actual environment. The invention further provides an indoor positioning system for RSSI ranging based on the iBeacons nodes.

The invention discloses an improved Kalman filtering algorithm-based indoor positioning system and method. The indoor positioning system comprises a plurality of anchor nodes, at least one unknown node, at least one collector node and a host computer. The unknown node sends data to anchor nodes therearound periodically, the anchor nodes acquire RSSI (Received Signal Strength Indication) values of the unknown node, the RSSI values received by all of the anchor nodes are screened through Gaussian filtering processing to obtain a value meeting a condition, the anchor nodes as well as location coordinates and ID information thereof are transmitted to the host computer through the collector node, distances corresponding to all of the RSSI values are calculated through the host computer, the distance values corresponding to the anchor nodes are subjected to the improved Kalman filtering processing, and coordinates of the unknown node are calculated through a trilateral positioning and centroid algorithm. Through adoption of the system and the method, the Kalman filtering algorithm is applied to indoor positioning, so that an excellent filtering effect is realized.

The present invention provides an improved DV-Hop positioning method based on the hop count threshold to optimize the average hop distance. Firstly, the hop count threshold is calculated, and considering the influence of other anchor nodes other than the nearest anchor node in the local and global ranges, the DV-Hop location is selected according to the threshold value. The optimal corrected average hop distance is used to estimate the distance, and after combined optimization of the anchor nodes within the single-hop communication radius participating in the positioning, the centroid algorithm is used to obtain an estimated coordinate, and the weighted least square method is used to obtain another estimated coordinate, and finally The arithmetic mean of the two estimated coordinates is used as the positioning coordinates of the unknown node. Simulation experiments show that the present invention can more effectively reduce the average node positioning error and improve the positioning accuracy.

The invention discloses a firefighter positioning method, system and device based on wireless sensing technology. Sensor nodes comprise reference nodes of the known location information and blind nodes of unknown location information in the network positioning process of the wireless sensor, the method comprises the following steps: firstly collecting the reference node location information when performing the blind nodes positioning, and then performing the ranging and positioning to obtain the node location; correcting ranging error and positioning error by mutually positioning reference nodes for a problem that the RSSI error is large under the non-line of sight situation at a fire protection spot; compensating the error when positioning the blind nodes, thereby effectively reducing theerror caused by the ranging and the error caused by the positioning algorithm itself; secondly, improving the positioning precision through a weighted-centroid algorithm based on the quantum particleswarm for the problem that the positioning algorithm based on the RSSI ranging or dispensing with the ranging is low in positioning precision. The firefighter positioning method, system and device based on wireless sensing technology disclosed by the invention can be extensively applied to the sensing field.

The invention provides a wireless sensor network three-dimensional node positioning method based on a tunneling method. The method includes the steps of 1, initializing a wireless sensor network, for each node, acquiring a distance between one-hop neighbor nodes, including the former node, and acquiring an anchor node coordinate matrix C; 2, calculating absolute coordinate matrixes Xi and Xj of the one-hop neighbor nodes; 3, calculating a target function Sigma(Xj) at the absolute coordinate matrix Xj; 4, if the former node is an unknown one, acquiring coordinates of the former node by means of a centroid algorithm to form an anchor node, and transmitting the coordinates to all one-hop neighbor nodes; 5, repeating the steps from 1 to 4 to finish positioning till all nodes turn into anchor nodes. The method has the advantages that the problem of the existing positioning methods that error accumulation occurs due to a computation process complicated by increase in dimensionality of a three-dimensional space can be solved, positioning error is small, and positioning precision is high.

The invention relates to a robust image hashing method and device based on Radon transformation and invariant features, and belongs to the field of information safety. In terms of the problem that hashing cannot resist geometric attacks well, normalized preprocessing operation is carried out on images firstly, invariant feature points are generated by utilizing an unchanged centroid algorithm, the circular area around an unchanged centroid is selected, Radon transformation is carried out on the circular area to generate a coefficient matrix, multiple lines of coefficients are selected randomly from a transformation domain by utilizing a chaotic system, robust features of each line are extracted, the features of all lines are combined with the invariant moment features of the whole matrix to generate image hashing, and similarity comparison is carried out by utilizing Euclidean distance. By the adoption of the robust image hashing method and device based on the Radon transformation and invariant features, the problem that the false drop rate rises due to geometric attacks can be solved effectively; the problems that computation complexity is too high and hashing is too long can be solved according to hashing steps and hashing lengths. The method and device can be applied to the field of image content authentication, and can also be applied to image retrieval, image identification and other information safety fields.

The invention belongs to the field of indoor positioning, and particularly relates to a multimode hybrid indoor positioning method. The method adopts a signal transmitting base station and a signal receiving end, wherein the signal transmitting base station transmits multimode hybrid signals which are received by the signal receiving end and determining the position of the signal receiving end. The method comprises the following steps: S1, uniformly recognizing and transcoding multimode hybrid signals to obtain coarse granularity signals, and receiving the coarse granularity signals by the signal receiving end; S2, preliminarily correcting the coarse value of an RSSI (Received Signal Strength Indicator); S3, adopting a mean signal secondary correction method based on a stack set; and S4, modeling and calculating with a triangular centroid algorithm to obtain the position of the receiving end. According to the method, three-in-one hardware integration and algorithm development are performed on WiFi positioning, Bluetooth positioning and radio frequency identification positioning technologies to overcome mutual defects, so that the accuracy of positioning and navigation is improved and high comprehensive performance is realized.

The invention discloses an optical precision tracking detector based on a double pyramidal rectangular pyramids, which comprises an imaging lens, a pyramidal rectangular pyramid with an opening in thecenter thereof, a dynamic range matching lens, a precision matching lens, a light spot amplification lens, a dynamic range light intensity detector, a precision pyramidal rectangular pyramid and a precision light intensity detector, wherein the traditional optical precision tracking detector based on the pyramidal rectangular pyramid is added with the centrally-opened pyramidal rectangular pyramid, the dynamic range matching lens and the dynamic range light intensity detector in the hardware manner to increase the dynamic range of the detection in the oblique direction of wavefront tilt, andin the software manner, the nested four quadrant light spot centroid algorithm is used for calculating the centroid of the light spot so as to restore the tilt angle or the tilt direction of target wavefront. The light intensity detector of the optical precision tracking detector has flexible selectivity, high detection precision, large dynamic range of the detection in the oblique direction of wavefront tilt, simple algorithm for restoring the wavefront tilt and easily-realized process, thus providing conditions for the detection of weak light wavefront at high accuracy and high frame frequency.

The invention discloses a WLAN (Wireless Local Area Network) fingerprint positioning method based on RSS (Really Simple Syndication) linear correlation and a re-weighted centroid algorithm. The method comprises the following steps of firstly, establishing an offline fingerprint database, arranging Q reference points in a target positioning environment, collecting multiple groups of RSS samples at the reference points and carrying out filtering processing, and generating a fingerprint database for describing the reference points; and then positioning at the environment, computing linear correlation coefficients of real-time RSS data received by a user terminal and fingerprint database sample data, selecting the reference points corresponding to k maximum correlation coefficients and adopting the re-weighted centroid algorithm to estimate a final position of a user. According to the method, the influence of the terminal hardware difference on the indoor positional accuracy can be reduced, and the stability and the accuracy of an indoor positioning system are effectively improved.

The invention discloses a vehicle-road cooperation-based tracking and positioning system and a tracking and positioning method for vehicles in a tunnel, and relates to the technical field of vehicle tracking and positioning in the tunnel. The roadside node obtains the field intensity RSSI sent by the vehicle-mounted unit and sends the field intensity RSSI to the distance calculation unit; The distance calculation unit establishes an RSSI-D model according to the field intensity RSSI,calculates the distance between the road side node and the vehicle, and sends the distance between the road sidenode and the vehicle to the positioning unit; And the positioning unit calculates the position of the vehicle by combining a weighted centroid algorithm according to the distance between the roadsidenode and the vehicle. A spread spectrum communication technology is adopted as a positioning means, compared with a traditional wireless positioning scheme, the position of a vehicle in a tunnel canbe monitored in real time, and long-distance positioning and multi-target simultaneous positioning can be achieved; Accurate sensing of vehicle positions in weak signal areas such as a tunnel is achieved, the method is applied to the fields of intelligent traffic and automatic driving, the problem that accurate positioning cannot be achieved in the tunnel is solved, positioning precision is high,and the application range is wide.

The invention belongs to the technical field of star extraction, and specifically relates to a star extraction method based on energy distribution. The star extraction method comprises following steps: images are scanned successively, and grey values of the imagines are compared with threshold value S; if the grey value of an image element is larger than S, then a nearby 3X3 image element area is searched; it is determined that in the 3X3 image element area whether the grey values of p image elements are larger than T; if it is determined that in the 3X3 image element area the grey values of p image elements are larger than T, then a star centroid is extracted from a nearby 5X5 area via centroid algorithm, otherwise scanning is carried out continuously. The star extraction method is capable of increasing accuracy of star centroid extraction; simultaneous performing of the two star map dividing stages and centroid algorithm can be realized; and real-time performance of star map processing is improved.

The invention discloses an indoor positioning method based on WiFi, Bluetooth and pedestrian dead reckoning (PDR) fusion, and the method is characterized in that the method comprises the following steps: 1) dividing a positioning region, and building a WiFi offline fingerprint data 2) clustering the training samples to obtain a centroid-like vector; 3) adopting a hierarchical clustering algorithm to obtain positioning coordinates; (4) achieving Bluetooth positioning by adopting an improved weighted centroid algorithm, (5) obtaining a WiFi and Bluetooth fusion positioning coordinate by fusing WiFi and Bluetooth positioning, and (6) obtaining a final positioning coordinate in combination with PDR. The method has the characteristics of high positioning precision and low software calculation amount, and can meet the real-time positioning precision requirement.

The invention provides a method for detecting influences of the gravity on the optical axis direction of a lens. According to the invention, a self-collimation technique of an optical system of the lens is utilized, a light source and a receiving device are installed on a focal plane of the optical lens, and a small-plane reflecting mirror and a pyramid prism are additionally arranged at a light inlet of the lens. The central positions of a light spot formed by the reflected light of the small-plane reflecting mirror on the receiving device and a reference light spot formed by reflected lightof the pyramid prism by using an image centroid algorithm, and the change of the optical axis direction can be obtained with high precision according to the change in central position of the light spot before and after the optical axis direction changes.