TWM335678U - Augmented navigation system of a moving object - Google Patents

Description

M335678 VIII. New description: [New technical field] This creation is about a navigation system, in particular, a navigation system in which a moving object can be accurately positioned in an invisible area. [Prior Art] The Global Positioning System (GPS) is a known navigation system that can accurately locate moving objects in areas where satellite signals are reachable; however, in areas where satellite nicknames are not available, for example ' In the basement, on the way, or in the presence of interference and obscuration, the satellite signal will fail to locate. The Inertial Navigation System (INS) is another known navigation system that allows for automatic operation and is unaffected by terrain. After initializing the starting position, the inertial navigation system can output information such as the position, speed, and direction of the moving object. However, its navigation solution drifts with time, causing navigation errors to increase. The combination of global positioning system and inertial navigation system into a composite navigation system can use the short-time navigation precision of INS to compensate GPS navigation error; in addition, the long-term navigation accuracy of GPS is used to compensate the error of INS navigation error with time. Taiwan Patent No. 489,212 (U.S. Patent No. 6,167,347) discloses a positioning and 'aircrafting method, which couples a global positioning system (Gps) with an inertial measurement unit (IMU) 'and utilizes a ^man filter (Kalman Filter) The GPS and IMU signals are combined to improve the accuracy of the combined positioning and navigation system, and the IMU can be used to assist in the loss of the star signal. In other words, the IMU signal is used to enhance or supplement the GPS signal, so the positioning and navigation of the 5H patent is still only applicable to the area where the satellite signal is reachable. 5 M335678 = Patent us 7,117, _ for -_, object in the navigation system. When the moving object is located in the invisible area, the linear distance is calculated by the displacement amount and direction of the unit time, and the map is combined with the map to calculate the position of the moving body. Fine, the speed of the moving object, the squared position, there will be obvious error in the estimated position. 6 and * #湾 patent 1284193 discloses a navigation system and a correction method for a vehicle, which mainly uses GPS as a navigation reference 'coordination-gyro device to obtain a direction and angle of a vehicle' and combines - an electronic map to calculate a vehicle Position, according to which the correction error is achieved. However, how positioning and navigation should be performed when the GPS signal disappears is not disclosed in the patent. Taiwan patent 125 隐 — 种 种 种 种 种 种 种 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四 四However, the patent does not teach how to perform positioning and navigation in areas that are not detected by GPS. U.S. Patent No. 6,826,477 discloses a pedestrian navigation method and apparatus. It uses a physiological model of the input pedestrian (PhySi〇i〇gicai characteristics) state to form a walking model (Step Model), and then uses the inertial detection device to detect the acceleration and direction of the pedestrian in various directions, and to detect the position of the pedestrian by GPS. The data is entered into the walking mode to predict the position, speed and direction of the pedestrian. The face value of the walking mode and the GPS smashing can be combined by the card_man filter test data. However, there is no teaching in this patent how to perform M335678 line positioning and navigation in areas not detected by GPS. [New content] This creation provides an innovative method and system to solve the shortcomings of the prior art because the previous technology touches GPS without trust, and the accuracy of navigation and positioning is insufficient. The author of this creation is to provide a precise navigation system and method for moving objects. It has a front-end platform for providing data and inertial side data; a back-end platform has an - predictor for data fusion and prediction. - the wireless network is used to transfer the data of the front-end platform to the back-end platform; and the error model (_r model) is configured on the end platform or the back-end platform for reading the fat data and the inertial detection bedding A gift-mathematical model; when the secret body enters the invisible area, the input-initial value or the input value is generated in the riding type to generate a correction value, and the correction value is input to the estimated H and the difficult side. Fusion to form the "estimated position to correspond to the age of the moving object - the misunderstanding and miscellaneous. ~ The following is a description of the preferred embodiments and the detailed description in accordance with the purpose, function and configuration disclosed in the present invention. [Embodiment] Referring to Figure 1, a navigation system 10 includes a GPS receiver 12 for receiving binary data transmitted from at least one artificial satellite 11. An inertial detecting device 14 is used for the speed, distance, direction and angle of the moving object. The moving object contains a moving car, a moving cargo or a moving person, and the like. M335678 The GPS receiver 12 and the inertial detection device 14 are respectively coupled to a central processing unit 16, and the data received by the GPS receiver 12 and the data detected by the inertial detection device 14 are respectively transmitted to the central processing unit. 16. The inertial detecting device 14T includes an accelerometer 142, an electronic compass 144, and a gyroscope 146. A wireless transmission module 18 is coupled to the central processing unit 16 for transmitting the GPS data and the accelerometer 142, the compass 144, and the data measured by the gyroscope 14. The global positioning system receiver 12, the inertial detection device 14, the central processing unit 16 and the wireless transmission module 18 are disposed in a portable device or a stationary device and define the device as a Front-end platform 2〇. The backend platform 30 includes a number receiver 32 for receiving messages from the front end platform 20. The error model 36 is coupled to the UI receiver & and is capable of reading the message output by the front end platform 20 as a reference value. And the error model 36 is an acceleration and a square of a moving object known by an accelerator, such as an accelerator, a gyroscope, and an electronic compass. The method of the __minute operation of the scatter method converts the acceleration and orientation (4) information into the information of the money and the transfer. The back-end platform 3G is: owing to the ride - the number of calculations remaining _ the speed, azimuth and position are related to the position of the previous observation point. The time interval between two adjacent observation points can be set to be the same. For example, the interval of the operation time can be _ leap seconds when the GPS operation completes the reference reference. In the same day, the relative speed, azimuth and position calculated by the 8 M335678 back-end platform 30 are compared with the current absolute position, velocity, and azimuth calculated by the sensor under good reception. Then, an error correction amount is generated, and after the statistical analysis mode, a sensor average error offset (ΔΧη) is further obtained. When the GPS receiver enters the weak or no-receiving zone, the back-end platform 3 utilizes the acceleration || 142 received by the inertial detecting device 14, the gyroscope (GylO Me (four) 146 and the electric

The sub-compass 144 data is input as an initial value or an input value to the error model 36 to generate a sensor average error offset "where", the sensor average error offset 篁 and the initial value Or enter the value and then enter a predictor (such as EKF, _ staff coffee 『, filter 'unscented 仙印 异' with the skills of the road painting and the map of the shouting of the lock Wei, for the correction of the drift position, 峨The effect of the positioning is as follows: V~疋'. If the message of the end platform 2〇 contains the gps data and the detection data of the inertial debt measuring device, the moving object is located in the Gps extractable area (visible area), This miscellaneous type % performs data analysis and the number of non-rounded sensor average error offsets (ΔΧη). Jianren does not. 忒 Estimate & 34 series link the signal receiver % with the error model %. The message=receipt 32 and the error model % respectively transmit the output message of the front end platform 2G and the average rank difference offset (Δχη) to the predictor, %, and each; Fusion and Produce - Estimated Position One Shows Cry 38 Link to the Estimate Cry W ρ^ Not for 38 ^ An electronic map 39 is used to display the position of the moving object. 9 M335678 A wireless network 40 is located between the front platform 2 and the back platform Deng to enable the output information of the front platform 20 to be borrowed. The wireless network 4 is transmitted to the backend 'platform 40. The wireless network can be a GMS network, a GPRS network, a zigbee. a network, a Bluetooth network, or a combination thereof. . The actual fineness and the front-real pay** are to arrange the error model 36 in the front end platform 20. The error money type 36 _ lining GPS receives n 12 positioning data and the detection of the inertial detecting device 14 The data is generated according to each data-mathematical model. When only the inertia_device 14 transmits the side data to the surface type 36, the error model 36 generates and outputs a sensor average error offset (Δzhen. The data and the correction value of the side device 14 are transmitted to the back-end platform 3 by the wireless transmission module 18 and the wireless network 40. The predictor % receives the data and then generates and generates a pre-mixed data. Estimate the position. Μ上_露_估计11 34 can be - hardware, - software or - take Body, • For example, KalmanFilter is used to fuse data; and the back-end platform 3〇 can be a personal computer (PC) or a server. - About the "axis object in the non-new area inspection and transport secrets The principle of prediction - as follows · ···. See the figure in Figure 3A's figure - the description of the positioning of the moving object by GPS and its motion trajectory, such as P1, P2, Pm^== domain... In the area A and the area c, the positioning and motion data of the Gps can be clearly defined, and the ', ,, and D, and the invisible area, such as the area, are displayed as blank areas because the M335678 bit data cannot be obtained. > ] Figure 3B' shows the description of the position and movement of the absolute position of the moving object in gPS. 2, P3...Pn), and also shows the relative position detection of the inertial detection. Description of the execution of the movement (Q1, Q2

m. In the area a and the area c, the gps positioning data and the inertia_device M, the bedding material are displayed, so two different but close curves are displayed, and the corresponding capital=points) are combined, because the inertial detecting device The detection data will change the deviation. For each detection position, there is an error offset (ΔΧ) between the GPS data and the inertial detection data, and it satisfies: P=Q+AX (1) in area B Inside, although GPS positioning cannot be obtained (4), the mosquito inertia price measuring device can still play the side Wei and provide the side (4). Therefore, based on the detection/work material of the inertial sampling device, we use the error area to find the average error of the sensory area.

Offset 篁 (fun), the generation equation (1) produces an estimated position secret (4) p〇邠 plus, EP) as follows: EPn = Qn + AXn (2) where η represents the estimated order produced in the invisible area And n-丨. Δχι is the average error offset of the sensor generated by the last Gps data and the inertia of the moving object before entering the invisible region as an initial value input to the §Houwu difference model; When η$2 'EPn-1 and Qn are an input value, the error model is input to generate ΔΧη. The manner in which the error model is established has been described in the previous description. 0 11 M335678 Please refer to Fig. 4'. The positioning and navigation method for the moving object is as follows: Step S51 is to read the GPS data and the inertia_data program. Among them, the nature of the poor material contains the shift __ position, direction, speed and acceleration size (four), and Lai _ clear material can be used to tear her P顚_) by the county data processing program to perform noise filtering phase se f fine · correction) and digitization (digitizatiQn).

Step S52 is a discrimination process for the area where the moving object is located. If the fat and the inertia are read, the data is located in the visible series, so that the back platform can display the position and motion track of the moving object according to the GPS data. If only the inertia_data can be read, it is determined that the moving object is in the -invisible area, and at this time, the generation procedure of the predicted correction value is entered. Step S53 is a program for generating a prediction correction value. The moving object

The GPS data includes the position observation value and the motion state observation value of the moving object; the last--Gps material and inertial detection data before entering the invisible area are input values/initial values, and the short reading/first tearing A sensor-averaged error offset ΔΧη is generated by calculation of the fine beam. Step S54 is a position and motion trajectory prediction procedure of the moving object in the invisible area. It is formed by integrating the inertial detection data with the prediction correction value in the -predator to form an estimated position (ΕΡ). The estimated position (4) can be displayed on the display. In addition, if the system disclosed in this creation still reads only inertia detection over time, the material indicates that the moving object has not left the invisible area. The estimated position value (ΕΡ) is the input value in the predictive correction value program disclosed in step S53 and is matched with the error 12 M335678 , \ .疋 ” When the moving object is in the invisible area, the system can generate a plurality of difficult positions to display the money and the position and movement.

Because the system and method disclosed in the present invention can display the position and motion state of the secreted body in an invisible area that cannot be observed by the GPS, so that the camera can be accurately mounted and navigated. Combined with the navigation H as a traveler, climber or rescuer; with the electronic reward to become the navigation of the vehicle' plus the wireless network can achieve the vehicle's tracking and monitoring, and set up 5 memories The body element can be used as a driving recorder. The above is the better _ and the design of the creation. However, the preferred embodiment and the design diagram are the stipulations of the squad, and the stipulations of the stipulations of the stipulations of the syllabus The scope of the rights covered by the contents of the "Scope of Application for Patent Application" is not within the scope of this creation and is the scope of the applicant's rights.

Mode [Simple description of the diagram] Figure 1 is a schematic diagram of one of the navigation systems of this creation. Figure 2 is a schematic diagram of another navigation system of the present creation. The 3A map is a schematic diagram showing the position and motion state of a moving object in the visible region. Figure 3B shows the navigation system of the present invention showing a position and motion state of a moving object in an invisible area. Figure 4 is a flow chart of the navigation method of the present creation. 13 M335678 11 artificial satellite 14 inertial detection device 144 compass 18 wireless transmission module 30 back-end platform 34 predictor 38 display [main component symbol description] ίο navigation system 12 global positioning system receiver 142 accelerometer 146 gyroscope 16 central Processing unit 20 front end platform 32 signal receiver 36 error model 39 electronic map 40 wireless network S51 reading GPS data and inertial detection data program S52 is the moving object area determination program S53 is a program to generate a prediction correction value S54 Position and motion obstruction prediction program for moving objects in invisible areas

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Claims (1)

M335678 IX. Patent application scope: 1. A precise navigation system for moving objects, which is used to display the position and motion trajectory of the moving object, and includes: a shovel platform is disposed in the moving object' which has a central processing a unit, a GPS receiver and an inertial detection device coupled to the central processing unit, and a wireless transmission module coupled to the central processing unit; a back-end platform having a signal receiver and a display respectively coupled to an estimator The signal receiver is configured to receive an output signal of the front platform, the predictor is configured to process a round-out message from the front platform, and the display is used to display the output information of the predictor; Between the front platform and the back end platform, the output signal of the front platform is transmitted to the signal receiver of the back platform; and an error model is established on the front platform and the back end One of the platforms and is connected to the central processing unit or predictor. 2. The precise navigation system for a moving object according to claim 1, wherein the inertial detecting device comprises an accelerometer, an electronic compass and a gyro and is coupled to the central processing unit. 3. The precise navigation system for a moving object according to claim 1, wherein the error model is a software body, a hardware body or a firmware body for squeezing the GPS receiver with the inertia The detection device detects the data for discrete mathematical accumulation and/or integration operations. 4. The precise navigation system for a moving object as described in claim 1, wherein in the 15 M335678, the wireless network comprises a GSM network, a GPRS network or a Zigbee network. 5. The precise navigation system for a moving object according to claim 1, wherein the back end platform is a computer or a server. 6. The precise navigation system for a moving object according to claim 1, wherein the predictor comprises a filter and a wave filter. 16