CN111679297A - Noise point drift removal method for GPS positioning track - Google Patents
Noise point drift removal method for GPS positioning track Download PDFInfo
- Publication number
- CN111679297A CN111679297A CN202010384702.XA CN202010384702A CN111679297A CN 111679297 A CN111679297 A CN 111679297A CN 202010384702 A CN202010384702 A CN 202010384702A CN 111679297 A CN111679297 A CN 111679297A
- Authority
- CN
- China
- Prior art keywords
- point
- drift
- points
- noise
- distance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/21—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/35—Constructional details or hardware or software details of the signal processing chain
- G01S19/37—Hardware or software details of the signal processing chain
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Navigation (AREA)
Abstract
The invention provides a method for removing noise point drift of a GPS positioning track, which comprises one or more of the following processes: s1: removing noise drift singular points which do not accord with geometric characteristics; s2: removing drift points with acceleration approximately equal to the acceleration of gravity; s3: removing drift points of which the movement distance is greater than the estimated distance of the pedometer; s4: removing adjacent drifting points with small adjacent distances; s5: and carrying out smooth filtering on the positioning track to smooth the geometric abrupt change noise points. The method introduces a geometric algorithm, accelerometer fusion positioning, pedometer fusion positioning, repeated point removing and smooth filtering, is more intelligent, and can remove more than 99% of track drift points, so that the positioning track is closer to a real track, the visualization effect is better, the correction of real-time positioning can be performed, and the correction of playback track can also be realized.
Description
Technical Field
The invention relates to the technical field of GPS, in particular to a method for removing noise point drift of a GPS positioning track.
Background
A Global Navigation Satellite System (GNSS) is a Satellite System that can provide Global, all-weather, and all-time high-precision geographical position information and Navigation and time service information. This is a satellite system consisting of 24 satellites covering the world. The system can ensure that 4 satellites can be observed at any point on the earth at any time, so that the satellite can acquire the longitude and latitude and the height of the observation point, and functions of navigation, positioning, time service and the like can be realized. This technique can be used to guide aircraft, ships, vehicles, and individuals to safely and accurately follow a selected route to a destination on time. The four global satellite navigation systems of GPS, GLONASS, BDS and GALILEO have been able to continuously provide navigation positioning services to various users. Under the conventional condition, the positioning precision of the GPS is very high, and after the modernization is completed, the navigation positioning service of a sub-meter level can be provided for global users.
In addition, noise interference of data received instantly by a GPS transmitter and a receiver can also cause noise drift points on the GPS positioning track. Furthermore, movement of the GPS receiver may cause jitter in the received data resulting in noisy offset points of positioning. These noise offsets will cause positioning errors and affect the next various applications based on positioning, such as navigation applications. Therefore, it is necessary to remove the GPS noise offset for positioning and its application.
At present, the main method for removing noise drift points is fusion positioning of various GNSS systems, such as Beidou/GPS fusion positioning, but the fusion positioning has the following difficulty: 1) unification of different coordinate systems is required; 2) unification of time scales is required; 3) a more complex star selection algorithm is required; 4) when the satellite searching signal quality of the GPS signal is not good, the satellite searching signal quality of the Beidou is not good, so that the optimization effect of fusion positioning is limited.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
The invention aims to provide a method for removing noise point drift of a GPS positioning track so as to solve the problem of singular point drift in the middle of the positioning track.
In order to achieve the purpose, the invention provides the following technical scheme:
a noise point drift removing method for a GPS positioning track comprises one or more of the following processes:
s1: removing noise drift singular points which do not accord with geometric characteristics;
s2: removing drift points with acceleration approximately equal to the acceleration of gravity;
s3: removing drift points of which the movement distance is greater than the estimated distance of the pedometer;
s4: removing adjacent drifting points with small adjacent distances;
s5: and carrying out smooth filtering on the positioning track to smooth the geometric abrupt change noise points.
Further, the method for removing the noise that does not conform to the geometric features in the process S1 is as follows:
a1. traversing all the points by using a computer algorithm, and respectively calculating the distance d1 between the point and the previous point, the distance d2 between the point and the next point and the distance d3 between the previous point and the next point for any given point;
a2. judging whether the sum of d1 and d2 is more than 1.5 times d 3;
a3. if the value is larger than the preset value, the point is indicated as a geometric drift point, and the point is deleted.
Further, the method for removing the drift point of the acceleration approximately equal to the gravitational acceleration in the process S2 is:
b1. collecting acceleration values of the accelerometers at the same moment;
b2. calculating an absolute value of a difference between an acceleration value and a gravitational acceleration
b3. If the absolute value of this difference is less than 0.2, then the point is considered to be the resting point and the point is considered to be the drift point deletion.
Further, the method for removing the drift point of which the movement distance is greater than the estimated step counter distance in the process S3 is as follows:
c1. collecting the step counting number of the pedometer between two adjacent points;
c2. if the counting number is in the range of [2,10000], the process is considered as a walking state;
c3. if the walking state is detected, calculating the step number 1.0m as the maximum walking distance;
c4. and if the distance between adjacent positioning points is greater than the maximum walking distance, regarding the point as a noise point, and deleting the noise point.
Further, the method for removing the adjacent drift points with small adjacent distances in the process S4 is as follows:
d 1: calculating the distance between two adjacent points;
d 2: if the distance between two adjacent points is smaller than a set threshold value, the motion of the point is considered to belong to noise motion, and the point is considered to be stationary;
d3. the noise motion point is deleted.
Further, the method for performing smooth filtering on the positioning track to smooth the geometric abrupt change noise point in the process S5 is:
e 1: carrying out smooth filtering with adjacent 5 points as filtering units on the positioning track;
e 2: the filtered track can reduce the interference of white noise and is a positioning track closer to a real track.
The invention can greatly delete a large number of singular points in the GPS positioning track by the noise point removing method, so that the final positioning track is clearer, more reasonable and more accurate.
The method is not only suitable for removing the track noise points of the GPS, but also generally suitable for removing the positioning track noise points of four global satellites of the GPS, the GLONASS, the BDS and the GALILEO, and simultaneously, the method is also suitable for removing the noise points of indoor positioning, including noise point removal in the fields of geomagnetic positioning, wifi positioning, zigbee positioning, UWB positioning, Bluetooth positioning, RFID positioning, ultrasonic positioning and the like.
The working principle of the invention is as follows: all the positioning systems are highly similar, and based on a given positioning system, the positioning tracks are collected, and then noise drift points are removed based on the positioning tracks, so that the positioning tracks are closer to the real situation.
Compared with the prior art, the invention has the following beneficial effects: 1. the invention introduces a geometric algorithm, accelerometer fusion positioning, pedometer fusion positioning, repeated point removal and smooth filtering, and is more intelligent; 2. the invention does not depend on the improvement and the upgrade of the hardware of the GPS, but carries out the auxiliary noise point removal from other dimensions; 3. the method can remove more than 99% of track drift points, so that the positioning track is closer to a real track, and the visualization effect is better; 4. the method has low calculation complexity, and can realize real-time drift point removal on common calculation equipment; 5. the method can not only correct the real-time positioning, but also correct the playback track.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for removing noise point drift of a GPS positioning track according to the present invention.
Detailed Description
The invention is further described with reference to the following drawings and detailed description:
example 1:
as shown in FIG. 1, a method for removing noise point drift of GPS positioning track comprises
S1: and removing noise drift singular points which do not accord with the geometrical characteristics.
The method for removing the noise that does not conform to the geometric characteristics in the process S1 is:
a1. traversing all the points by using a computer algorithm, and respectively calculating the distance d1 between the point and the previous point, the distance d2 between the point and the next point and the distance d3 between the previous point and the next point for any given point;
a2. judging whether the sum of d1 and d2 is more than 1.5 times d 3;
a3. if the value is larger than the preset value, the point is indicated as a geometric drift point, and the point is deleted.
Example 2:
a method for removing noise point drift of GPS positioning track includes
S2: removing drift points with acceleration approximately equal to the acceleration of gravity;
the method for removing the drift point of the acceleration approximately equal to the gravitational acceleration in the process S2 is as follows:
b1. collecting acceleration values of the accelerometers at the same moment;
b2. calculating an absolute value of a difference between an acceleration value and a gravitational acceleration
b3. If the absolute value of this difference is less than 0.2, then the point is considered to be the resting point and the point is considered to be the drift point deletion.
Example 3:
a method for removing noise point drift of GPS positioning track includes
S3: and removing drift points of which the movement distance is greater than the estimated distance of the pedometer.
The method for removing the drift point of which the movement distance is greater than the estimated distance of the pedometer in the process S3 is as follows:
c1. collecting the step counting number of the pedometer between two adjacent points;
c2. if the counting number is in the range of [2,10000], the process is considered as a walking state;
c3. if the walking state is detected, calculating the step number 1.0m as the maximum walking distance;
c4. and if the distance between adjacent positioning points is greater than the maximum walking distance, regarding the point as a noise point, and deleting the noise point.
Example 4:
a method for removing noise point drift of GPS positioning track includes
S4: removing adjacent drifting points with small adjacent distances;
the method for removing the adjacent drift points with small adjacent distance in the process S4 is as follows:
d 1: calculating the distance between two adjacent points;
d 2: if the distance between two adjacent points is smaller than a set threshold value, the motion of the point is considered to belong to noise motion, and the point is considered to be stationary;
d3. the noise motion point is deleted.
Example 5:
a method for removing noise point drift of GPS positioning track includes
S5: and carrying out smooth filtering on the positioning track to smooth the geometric abrupt change noise points.
The method for smoothing the positioning track to smooth the geometric abrupt change noise point in the process S5 is as follows:
e 1: carrying out smooth filtering with adjacent 5 points as filtering units on the positioning track;
e 2: the filtered track can reduce the interference of white noise and is a positioning track closer to a real track.
The method is not only suitable for removing the track noise points of the GPS, but also generally suitable for removing the positioning track noise points of four global satellites including the GPS, the GLONASS, the BDS and the GALILEO, and meanwhile, the method is also suitable for removing the noise points of indoor positioning, including noise point removal in the fields of geomagnetic positioning, wifi positioning, zigbee positioning, UWB positioning, Bluetooth positioning, RFID positioning, ultrasonic positioning and the like.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that various changes, modifications and substitutions can be made without departing from the spirit and scope of the invention as defined by the appended claims. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A noise point drift removing method for a GPS positioning track is characterized by comprising one or more of the following processes:
s1: removing noise drift singular points which do not accord with geometric characteristics;
s2: removing drift points with acceleration approximately equal to the acceleration of gravity;
s3: removing drift points of which the movement distance is greater than the estimated distance of the pedometer;
s4: removing adjacent drifting points with small adjacent distances;
s5: and carrying out smooth filtering on the positioning track to smooth the geometric abrupt change noise points.
2. The method for removing the noise point drift of the GPS positioning track according to claim 1, wherein the method for removing the noise that does not conform to the geometric characteristics in the process (S1) is:
a1. traversing all the points by using a computer algorithm, and respectively calculating the distance d1 between the point and the previous point, the distance d2 between the point and the next point and the distance d3 between the previous point and the next point for any given point;
a2. judging whether the sum of d1 and d2 is more than 1.5 times d 3;
a3. if the value is larger than the preset value, the point is indicated as a geometric drift point, and the point is deleted.
3. The method for removing the drift of the noise point of the GPS positioning track according to claim 1, wherein the method for removing the drift point of the acceleration approximately equal to the acceleration of gravity in the process (S2) is:
b1. collecting acceleration values of an accelerometer in the same moment and different directions;
b2. calculating an absolute value of a difference between an acceleration value and a gravitational acceleration
b3. If the absolute value of this difference is less than 0.2, then the point is considered to be the resting point and the point is considered to be the drift point deletion.
4. The method for removing the noise drift of the GPS positioning track according to claim 1, wherein the method for removing the drift points with the moving distance greater than the estimated distance of the pedometer in the process (S3) comprises:
c1. collecting the step counting number of the pedometer between two adjacent points;
c2. if the counting number is in the range of [2,10000], the process is considered as a walking state;
c3. if the walking state is detected, calculating the step number 1.0m as the maximum walking distance;
c4. and if the distance between adjacent positioning points is greater than the maximum walking distance, regarding the point as a noise point, and deleting the noise point.
5. The method for removing the noise drift of the GPS positioning track according to claim 1, wherein the method for removing the adjacent drift points with small adjacent distance in the process (S4) is:
d 1: calculating the distance between two adjacent points;
d 2: if the distance between two adjacent points is smaller than a set threshold value, the motion of the point is considered to belong to noise motion, and the point is considered to be stationary;
d3. the noise motion point is deleted.
6. The method for removing the noise point drift of the GPS positioning track according to claim 1, wherein the method for smoothing the positioning track to smooth the geometrically abrupt noise point in the process (S5) is:
e 1: carrying out smooth filtering with adjacent 5 points as filtering units on the positioning track;
e 2: the filtered track can reduce the interference of white noise and is a positioning track closer to a real track.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010384702.XA CN111679297A (en) | 2020-05-08 | 2020-05-08 | Noise point drift removal method for GPS positioning track |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010384702.XA CN111679297A (en) | 2020-05-08 | 2020-05-08 | Noise point drift removal method for GPS positioning track |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111679297A true CN111679297A (en) | 2020-09-18 |
Family
ID=72452292
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010384702.XA Pending CN111679297A (en) | 2020-05-08 | 2020-05-08 | Noise point drift removal method for GPS positioning track |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111679297A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113777643A (en) * | 2021-07-30 | 2021-12-10 | 国网浙江杭州市余杭区供电有限公司 | Fault early warning method and device for preventing transmission line from being broken outside |
| CN116430423A (en) * | 2023-06-13 | 2023-07-14 | 广州悦跑信息科技有限公司 | Satellite navigation positioning track point coordinate method in motion data |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102749631A (en) * | 2012-07-26 | 2012-10-24 | 海华电子企业(中国)有限公司 | Method for reducing positioning drift of Big Dipper satellite navigating and positioning device |
| CN104215238A (en) * | 2014-08-21 | 2014-12-17 | 北京空间飞行器总体设计部 | Indoor positioning method of intelligent mobile phone |
| CN104977006A (en) * | 2015-08-11 | 2015-10-14 | 北京纳尔信通科技有限公司 | Indoor positioning method based on fuzzy theory and multi-sensor fusion |
| CN104992072A (en) * | 2015-07-21 | 2015-10-21 | 江苏北斗卫星应用产业研究院有限公司 | Operation land parcel automatic identification and area statistics method based on spatial mesh division |
| CN105511481A (en) * | 2014-11-26 | 2016-04-20 | 航天恒星科技有限公司 | Satellite borne orbit determination optimization method |
| CN105872987A (en) * | 2016-04-22 | 2016-08-17 | 浙江大学 | Method for node location of distributed wireless sensor network based on single mobile robot |
| CN105911542A (en) * | 2016-07-04 | 2016-08-31 | 中国人民解放军海军航空工程学院 | Hypersonic velocity target TBD detection method for polynomial Hough conversion |
| CN106500728A (en) * | 2016-10-26 | 2017-03-15 | 北京小鸟看看科技有限公司 | A kind of method for temperature drift compensation of gyroscope and device |
| CN106772458A (en) * | 2017-03-01 | 2017-05-31 | 北京电子工程总体研究所 | A kind of military anti-interference automatic navigator |
| CN107144280A (en) * | 2017-05-10 | 2017-09-08 | 深圳市沃特沃德股份有限公司 | The method and apparatus for recognizing anchor point |
| CN107248141A (en) * | 2017-04-28 | 2017-10-13 | 努比亚技术有限公司 | A kind of image edit method and device and computer-readable recording medium |
| CN108225184A (en) * | 2018-01-16 | 2018-06-29 | 上海同岩土木工程科技股份有限公司 | A kind of shield tunnel Point Cloud Data from Three Dimension Laser Scanning removes the method made an uproar |
| CN108931795A (en) * | 2018-05-21 | 2018-12-04 | 千寻位置网络有限公司 | Positioning equipment track optimization and boundary extraction method and device |
| CN109269514A (en) * | 2017-07-18 | 2019-01-25 | 华为技术有限公司 | The method and apparatus for determining motion profile |
| CN109917430A (en) * | 2019-04-03 | 2019-06-21 | 安徽中科智能感知产业技术研究院有限责任公司 | A kind of satellite positioning track drift method for correcting error based on smooth trajectory algorithm |
| CN109975839A (en) * | 2019-04-10 | 2019-07-05 | 华砺智行(武汉)科技有限公司 | A kind of Federated filter optimization method of vehicle satellite location data |
| CN110136072A (en) * | 2018-02-08 | 2019-08-16 | 北京大学 | Minimizing technology, denoising system, computer equipment and the storage medium of point cloud noise |
| CN110515936A (en) * | 2019-09-02 | 2019-11-29 | 北京首汽智行科技有限公司 | A method of optimization GPS data |
-
2020
- 2020-05-08 CN CN202010384702.XA patent/CN111679297A/en active Pending
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102749631A (en) * | 2012-07-26 | 2012-10-24 | 海华电子企业(中国)有限公司 | Method for reducing positioning drift of Big Dipper satellite navigating and positioning device |
| CN104215238A (en) * | 2014-08-21 | 2014-12-17 | 北京空间飞行器总体设计部 | Indoor positioning method of intelligent mobile phone |
| CN105511481A (en) * | 2014-11-26 | 2016-04-20 | 航天恒星科技有限公司 | Satellite borne orbit determination optimization method |
| CN104992072A (en) * | 2015-07-21 | 2015-10-21 | 江苏北斗卫星应用产业研究院有限公司 | Operation land parcel automatic identification and area statistics method based on spatial mesh division |
| CN104977006A (en) * | 2015-08-11 | 2015-10-14 | 北京纳尔信通科技有限公司 | Indoor positioning method based on fuzzy theory and multi-sensor fusion |
| CN105872987A (en) * | 2016-04-22 | 2016-08-17 | 浙江大学 | Method for node location of distributed wireless sensor network based on single mobile robot |
| CN105911542A (en) * | 2016-07-04 | 2016-08-31 | 中国人民解放军海军航空工程学院 | Hypersonic velocity target TBD detection method for polynomial Hough conversion |
| CN106500728A (en) * | 2016-10-26 | 2017-03-15 | 北京小鸟看看科技有限公司 | A kind of method for temperature drift compensation of gyroscope and device |
| CN106772458A (en) * | 2017-03-01 | 2017-05-31 | 北京电子工程总体研究所 | A kind of military anti-interference automatic navigator |
| CN107248141A (en) * | 2017-04-28 | 2017-10-13 | 努比亚技术有限公司 | A kind of image edit method and device and computer-readable recording medium |
| CN107144280A (en) * | 2017-05-10 | 2017-09-08 | 深圳市沃特沃德股份有限公司 | The method and apparatus for recognizing anchor point |
| CN109269514A (en) * | 2017-07-18 | 2019-01-25 | 华为技术有限公司 | The method and apparatus for determining motion profile |
| CN108225184A (en) * | 2018-01-16 | 2018-06-29 | 上海同岩土木工程科技股份有限公司 | A kind of shield tunnel Point Cloud Data from Three Dimension Laser Scanning removes the method made an uproar |
| CN110136072A (en) * | 2018-02-08 | 2019-08-16 | 北京大学 | Minimizing technology, denoising system, computer equipment and the storage medium of point cloud noise |
| CN108931795A (en) * | 2018-05-21 | 2018-12-04 | 千寻位置网络有限公司 | Positioning equipment track optimization and boundary extraction method and device |
| CN109917430A (en) * | 2019-04-03 | 2019-06-21 | 安徽中科智能感知产业技术研究院有限责任公司 | A kind of satellite positioning track drift method for correcting error based on smooth trajectory algorithm |
| CN109975839A (en) * | 2019-04-10 | 2019-07-05 | 华砺智行(武汉)科技有限公司 | A kind of Federated filter optimization method of vehicle satellite location data |
| CN110515936A (en) * | 2019-09-02 | 2019-11-29 | 北京首汽智行科技有限公司 | A method of optimization GPS data |
Non-Patent Citations (10)
| Title |
|---|
| 付强: "计步器测量日步行量综述", 《机械与电子》, no. 25, pages 95 - 96 * |
| 宣秀彬: "基于Wi-Fi和航位推算的室内定位方法研究", no. 2 * |
| 房兴博: "基于行人航位推算和多传感器融合的室内三维定位算法研究", no. 1 * |
| 曹振波: "发达国家体育健康政策发展及对健康中国的启示", 《体育科学》, vol. 37, no. 5, pages 135 - 15 * |
| 柴壮壮等: "出租车轨迹数据的挖掘与可视化", no. 1, pages 034 - 1228 * |
| 欧阳鸿等: "基于步行GPS轨迹的路网提取方法", no. 2, pages 124 - 128 * |
| 王伊冰: "三维行人自主导航融合算法研究", no. 3 * |
| 罗兰: "基于跑步App数据分析的西安市跑步线路空间分布研究", 《城市建筑》, vol. 19, no. 307, pages 19 - 21 * |
| 高业何敏: "基于GPS/DR/WiFi的室内外无缝定位研究", no. 5 * |
| 高静文: "运输车辆轨迹点数据清洗方法研究", vol. 15, no. 15 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113777643A (en) * | 2021-07-30 | 2021-12-10 | 国网浙江杭州市余杭区供电有限公司 | Fault early warning method and device for preventing transmission line from being broken outside |
| CN116430423A (en) * | 2023-06-13 | 2023-07-14 | 广州悦跑信息科技有限公司 | Satellite navigation positioning track point coordinate method in motion data |
| CN116430423B (en) * | 2023-06-13 | 2023-08-29 | 广州悦跑信息科技有限公司 | Satellite navigation positioning track point coordinate correction method in motion data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109946730B (en) | Ultra-wideband-based high-reliability fusion positioning method for vehicles under cooperation of vehicle and road | |
| CN109507677B (en) | SLAM method combining GPS and radar odometer | |
| Kim et al. | High-speed train navigation system based on multi-sensor data fusion and map matching algorithm | |
| CN107247275B (en) | Urban GNSS vulnerability monitoring system and method based on bus | |
| CN108802786A (en) | A kind of vehicle positioning method | |
| US9086288B2 (en) | Method and system for finding paths using GPS tracks | |
| CN113358112B (en) | Map construction method and laser inertia odometer | |
| CN113933818A (en) | Method, device, storage medium and program product for calibrating laser radar external parameter | |
| CN109633763B (en) | Precise geomagnetic mapping system based on magnetometer and GPS and geomagnetic mapping method thereof | |
| CN105674984A (en) | Method for acquiring advancing directions of pedestrians by aid of mobile terminals without constraints | |
| CN114018274A (en) | Vehicle positioning method and device and electronic equipment | |
| CN111679297A (en) | Noise point drift removal method for GPS positioning track | |
| CN112327340A (en) | Terminal positioning accuracy evaluation method, device, equipment and medium | |
| CN111256695A (en) | UWB/INS combined indoor positioning method based on particle filter algorithm | |
| CN111522034A (en) | Positioning method, equipment and device based on inertial navigation | |
| CN111121755B (en) | Multi-sensor fusion positioning method, device, equipment and storage medium | |
| CN109781120A (en) | A kind of vehicle combination localization method based on synchronous positioning composition | |
| CN114915913A (en) | UWB-IMU combined indoor positioning method based on sliding window factor graph | |
| CN109975848B (en) | Precision optimization method of mobile measurement system based on RTK technology | |
| CN107525523A (en) | Satellite navigation auxiliary SINS carries out the method and device of initial azimuth alignment | |
| CN114088080A (en) | Positioning device and method based on multi-sensor data fusion | |
| CN117119586B (en) | Indoor positioning fusion method based on UWB and IMU | |
| CN115129796A (en) | Positioning data analysis method, apparatus, device and medium | |
| CN111060064A (en) | Intelligent pipeline deformation detection system combining inertial navigation and triangulation positioning | |
| CN115435782A (en) | Anti-interference position estimation method and device under multi-source information constraint |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |