A WiFi-RTT positioning processing system and method based on global search noise reduction

Abstract

The present invention discloses a WiFi-RTT positioning processing system and method based on global search noise reduction, wherein the system includes a data acquisition system, a data preprocessing system, a reflection projection model system, a global search noise reduction system and a positioning solution system, wherein the data acquisition system collects and stores data into a data set; the data preprocessing system includes a mode discrimination monitoring system, a multipath removal system, a noise reduction system, and a reflection projection model system; the data in the data set is processed by the data preprocessing system to reduce the multipath effect and the influence of Gaussian noise, and pseudo data is obtained by using reflection projection processing, and the global search noise reduction system processes the pseudo data from a statistical perspective and preliminarily eliminates the phase distortion noise; finally, the positioning solution system obtains the positioning result and performs visualization processing. The present invention greatly reduces the influence of phase distortion noise on the positioning result by introducing a global search noise reduction model, and the positioning solution accuracy is improved by 15%.

Description

Technical Field

[0001] The present invention relates to the field of indoor positioning technology, and in particular to a WiFi-RTT positioning processing system and method based on global search noise reduction. Background Art

[0002] The application of location-based services has attracted more and more attention to positioning technology, and at the same time, higher requirements have been put forward for the accuracy of positioning results. With the popularization and application of smart phones, mobile phones that provide a variety of location-based services will become the main carriers of high-precision positioning for the public in the future. Since navigation signals based on the Global Navigation Satellite System (GNSS) are difficult to receive indoors, they cannot be used for indoor positioning. In order to solve the problem of indoor positioning, a variety of technical solutions have been proposed, such as those based on WiFi, ultra-wideband, Bluetooth, inertial sensors, etc. Compared with other technologies, WiFi has received more attention due to its large audience and low price. Distance measurement methods such as ToA and TDoA have serious deviations in distance measurement results due to clock errors, so it is extremely unreasonable to use them for positioning. The RTT distance measurement method can provide more accurate distance measurement results by eliminating the influence of clock errors, but it cannot obtain good positioning results due to the existence of semi-system errors. No reasonable solution has been proposed yet. Summary of the invention

[0003] The object of the present invention is to provide a WiFi-RTT positioning processing system and method based on global search noise reduction to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A WiFi-RTT positioning processing system based on global search and noise reduction, including a data acquisition system, a data preprocessing system, a global search and noise reduction system and a positioning solution system;

[0006] The data acquisition system is used to collect and store data into a data set, and the data acquisition system can retrieve all data of any link previously calculated; the data acquisition system transmits the data set to the data preprocessing system;

[0007] The data preprocessing system includes a mode identification monitoring system, a multipath removal system, a noise reduction system, and a reflection projection model system; the data in the data set is obtained by the data preprocessing system to reduce the multipath effect and noise influence compared with the original data; the reflection projection model system is used to obtain pseudo data by calculation using the reflection projection model; finally, the data preprocessing system passes all the obtained results to the global search noise reduction system;

[0008] The global search noise reduction system models the pseudo data through data comparison to obtain whitened data, and transmits the whitened data to the positioning solution system;

[0009] The positioning solution system is used to process the results, obtain the positioning results and perform visualization processing, and then send the positioning results and related information to the data set.

[0010] According to another aspect of the present invention, a WiFi-RTT positioning processing method based on global search noise reduction is proposed, comprising the following steps:

[0011] Step 1: The data acquisition system collects and stores data into a data set, and the data acquisition system can retrieve database information and add it to the data set;

[0012] Step 2, the data acquisition system transmits the data set to a data preprocessing system, the data in the data set is processed by the data preprocessing system, and the obtained data is data with reduced multipath effect and noise influence compared with the original data and expanded by the reflection projection model, and the obtained data is called pseudo data;

[0013] Step 3, the pseudo data is transmitted to the global search denoising system by the data preprocessing system, and the global search denoising system uses the global search denoising algorithm therein to obtain data for preliminary elimination of phase distortion noise from a statistical perspective through calculation, and the obtained data is called whitened data;

[0014] Step 4: Finally, the global search denoising system transmits all the whitened data to the positioning and solving system. The positioning and solving system processes the results, obtains the positioning results and performs visualization, and then sends the positioning results and related information to the data set.

[0015] Beneficial effects:

[0016] Compared with the prior art, the present invention processes data from a statistical perspective by introducing a global search noise reduction model, preliminarily eliminates phase distortion noise, greatly reduces the impact of phase distortion noise on positioning results, and improves positioning solution accuracy by 15%. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1is a schematic diagram of a WiFi-RTT positioning system based on global search noise reduction according to an embodiment of the present invention;

[0019] Figure 2 is a flow chart of a global search denoising algorithm according to an embodiment of the present invention.

[0020] Reference numerals:

[0021] 1. Data acquisition system; 2. Data preprocessing system; 3. Global search and noise reduction system; 4. Positioning solution system; 5. Data set; 6. WiFi data; 7. Inertial navigation data provided by the inertial navigation system; 8. Timestamp; 9. State principal component; 10. Database information; 11. Pattern identification and monitoring system; 12. Demultipathing system; 13. Noise reduction system; 14. Reflection projection model system; 15. Pseudo data; 16. Global search and noise reduction model; 17. Whitening data; 18. Positioning results and related information. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of the present invention.

[0023] According to an embodiment of the present invention, a WiFi-RTT positioning processing system based on global search noise reduction is provided. Figure 1 , the system includes a data acquisition system 1, a data preprocessing system 2, a global search and noise reduction system 3 and a positioning solution system 4;

[0024] The data acquisition system 1 is used to collect and store data into a data set 5, and the data acquisition system 1 can retrieve all data of any link previously calculated; the data acquisition system 1 transmits the data set 5 to the data preprocessing system 2;

[0025] The data preprocessing system 2 includes a mode identification monitoring system 11, a multipath removal system 12, a noise reduction system 13, and a reflection projection model system 14; the data in the data set 5 is obtained by the data preprocessing system 2 to reduce the multipath effect and noise influence compared with the original data, and the reflection projection model system 14 is used to obtain pseudo data 15 by calculation using the reflection projection model, and finally the data preprocessing system 2 passes all the obtained results to the global search noise reduction system 3;

[0026] The global search denoising system 3 models the pseudo data 15 through data comparison to obtain whitened data 17, and transmits the whitened data 17 to the positioning solution system 4; the global search denoising system 3 stores and is provided with a global search denoising model to implement a global search denoising algorithm.

[0027] The positioning solution system 4 is used to process the results, obtain the positioning results and perform visualization processing, and then send the positioning results and related information 18 to the data set 5.

[0028] According to another embodiment of the present invention, a WiFi-RTT positioning processing method based on global search noise reduction is proposed, comprising the following steps:

[0029] Step 1: The data acquisition system collects and stores data into a data set, and the data acquisition system can retrieve database information and add it to the data set;

[0030] Step 2, the data acquisition system transmits the data set to the data preprocessing system, the data in the data set is processed by the data preprocessing system, and the obtained data is data with reduced multipath effect and noise influence compared with the original data and expanded by the reflection projection model, and the obtained data is called pseudo data;

[0031] Step 3, the pseudo data is transmitted to the global search denoising system by the data preprocessing system, and the global search denoising system uses the global search denoising algorithm therein to obtain data for preliminary elimination of phase distortion noise from a statistical perspective through calculation, and the obtained data is called whitened data;

[0032] Step 4: Finally, the global search denoising system transmits all the whitened data to the positioning and solving system, and the positioning and solving system processes the results to obtain positioning results and performs visualization processing.

[0033] According to another embodiment of the present invention, the data set 5 includes WiFi data 6, inertial navigation data 7 provided by an inertial navigation system, a timestamp 8, and also includes retrieving database information 10 related to the current data from all previously calculated data of any link. Preferably, the related data includes the direction vector, distance, distance range, current motion state, etc. of the router and the mobile phone. The direction vector dirc and the current motion state are called state principal components 9.

[0034] According to one embodiment of the present invention, Figure 2 As shown, the global search denoising model 16 is used to implement a global search denoising algorithm, and the specific process of the algorithm includes the following steps:

[0035] S101: Obtaining a reference position L1; specifically, the existing noise reduction means may be used to perform basic processing on the data, firstly performing a data solution using the basically processed data, and using the solved position as the reference position;

[0036] S102: using the reference position L1, obtaining the distance between the reference position and the state principal component 9 of each router;

[0037] S103: performing a global search in the data set 5 according to the state principal component to obtain data having similar state principal components;

[0038] S104: Calculate the current distance according to the current reference position and the standard position of each router, remove the maximum value data of the fluctuation range determined by the semi-systematic error and the white noise through the current distance, obtain an alternative sequence, and perform weighted average on the distance of the alternative sequence; in the embodiment of the present invention, the range is determined by the two errors of the semi-systematic error and the white noise error, and this range is the tolerance range for the data quality. Within this tolerance range, the data is kept for backup, otherwise it is directly removed.

[0039] S105: loading and outputting the weighted average result to participate in the calculation of the positioning solution system;

[0040] According to an embodiment of the present invention, if the number of candidate sequences does not exceed a preset maximum value, no elimination is performed; otherwise, a random number is generated to select the candidate sequences with the preset maximum number.

[0041] According to one embodiment of the present invention, the positioning and solving system obtains the direction vector dirc, distance d and confidence range [da, d+a] between the standard position and each router, and saves the above information into a data set.

[0042] According to one embodiment of the present invention, the data having the state principal component 9 similar to the state principal component 9 needs to be obtained through principal component analysis, and a cost function calculation result is obtained. The normalized result of the cost function calculation result also affects the weighted result. The first weight coefficient is proportional to the normalized result. The cost function characterizes the degree of data information loss caused by replacing the original data with the principal component analysis result.

[0043] According to one embodiment of the present invention, a statistical percentage is obtained through the statistical relationship between the distance in step 102 and the distance in the alternative sequence data, and then the statistical percentage is normalized. The statistical percentage is normalized again, and weights are determined according to the normalized statistical percentage to obtain a second weight coefficient, the second weight coefficient is inversely proportional to the normalized statistical percentage, and the weighted average is the product of the normalized first weight coefficient and the second weight coefficient.

[0044] In summary, compared with the prior art, the technical solution of the present invention introduces a global search denoising model, processes the data from a statistical perspective, and preliminarily eliminates the phase distortion noise, which greatly reduces the impact of the phase distortion noise on the positioning results and improves the positioning solution accuracy by 15%.

[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A WiFi-RTT positioning processing method based on global search and noise reduction, using a WiFi-RTT positioning processing system based on global search and noise reduction, the system includes a data acquisition system, a data preprocessing system, a global search and noise reduction system and a positioning solution system; in, The data acquisition system is used to collect and store data into a data set, and the data acquisition system can retrieve all data of any link calculated previously; The data acquisition system transmits the data set to the data preprocessing system; The data preprocessing system includes a mode identification monitoring system, a multipath removal system, a noise reduction system, and a reflection projection model system; the data in the data set is obtained by the data preprocessing system to reduce the multipath effect and noise influence compared with the original data; the reflection projection model system is used to obtain pseudo data by calculation using the reflection projection model; finally, the data preprocessing system passes all the obtained results to the global search noise reduction system; The global search noise reduction system models the pseudo data through data comparison to obtain whitened data, and transmits the whitened data to the positioning solution system; The positioning solution system is used to process the result, obtain the positioning result and perform visualization, and then send the positioning result and related information to the data set, and is characterized by comprising the following steps: Step 1: The data acquisition system collects and stores data into a data set, and the data acquisition system can retrieve database information and add it to the data set; Step 2, the data acquisition system transmits the data set to a data preprocessing system, the data in the data set is processed by the data preprocessing system, and the obtained data is data with reduced multipath effect and noise influence compared with the original data and expanded by the reflection projection model, and the obtained data is called pseudo data; Step 3, the pseudo data is transmitted to the global search denoising system by the data preprocessing system, and the global search denoising system uses the global search denoising algorithm therein to obtain data for preliminary elimination of phase distortion noise from a statistical perspective through calculation, and the obtained data is called whitened data; Step 4: Finally, the global search denoising system transmits all the whitened data to the positioning and solving system. The positioning and solving system processes the results, obtains the positioning results and performs visualization, and then sends the positioning results and related information to the data set.

2. According to the WiFi-RTT positioning processing method based on global search noise reduction according to claim 1, it is characterized in that: In step 1, the data set includes WiFi data, inertial navigation data provided by the inertial navigation system, timestamp, and also includes retrieving database data related to the current data from all previously calculated data of any link, the related database data includes the direction vector, distance, distance range, and current motion state of the router and the mobile phone, and the direction vector dirc and the current motion state are called the state principal component.

3. According to the WiFi-RTT positioning method based on global search noise reduction according to claim 1, it is characterized in that: The global search denoising algorithm comprises the following steps: Step (3.1). Obtain the reference position L1; Step (3.2). Using the reference location L1, obtain the state principal components and distances between the reference location and each router; Step (3.3). Perform a global search in the database according to the state principal component to obtain data having similar state principal components; Step (3.4). Calculate the current distance based on the current reference position and the standard position of each router, remove the maximum value data of the fluctuation range determined by the semi-system error and white noise through the current distance, obtain the candidate sequence, and perform weighted average on the distance of the candidate sequence; Step (3.5). Load the weighted average result into the output result to participate in the calculation of the positioning solution system.

4. According to the WiFi-RTT positioning processing method based on global search noise reduction according to claim 3, it is characterized in that: If the number of data included in the candidate sequence does not exceed the preset maximum value, no data is eliminated; otherwise, a random number is generated to select the candidate sequence with the preset maximum number.

5. According to the WiFi-RTT positioning processing method based on global search noise reduction according to claim 3, it is characterized in that: The positioning and solving system obtains the standard position and the direction vector dirc, the distance d and the confidence range [da, d+a] of each router, and saves the above information into the data set.

6. The WiFi-RTT positioning processing method based on global search noise reduction according to claim 3 is characterized in that: The data having principal components similar to the state needs to be obtained through principal component analysis and the cost function calculation result is obtained. The normalized result of the cost function calculation result also affects the weighted result. The first weight coefficient is proportional to the normalized result. The cost function characterizes the degree of data information loss caused by replacing the original data with the principal component analysis result.

7. The WiFi-RTT positioning processing method based on global search noise reduction according to claim 3 is characterized in that: The statistical percentage is obtained through the statistical relationship between the distance in step (3.2) and the distance in the alternative sequence data, and then the statistical percentage is normalized. The weight is determined according to the normalized statistical percentage to obtain a second weight coefficient, and the second weight coefficient is inversely proportional to the normalized statistical percentage. The weighted average is the product of the normalized first weight coefficient and the second weight coefficient.

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