CN113438731B - Positioning method and system based on signal quality control and characteristic fingerprint enhancement - Google Patents
Positioning method and system based on signal quality control and characteristic fingerprint enhancement Download PDFInfo
- Publication number
- CN113438731B CN113438731B CN202110652675.4A CN202110652675A CN113438731B CN 113438731 B CN113438731 B CN 113438731B CN 202110652675 A CN202110652675 A CN 202110652675A CN 113438731 B CN113438731 B CN 113438731B
- Authority
- CN
- China
- Prior art keywords
- fingerprint
- positioning
- quality control
- information
- signal quality
- 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.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention provides a positioning method and a system based on signal quality control and characteristic fingerprint enhancement, comprising the following steps: the characteristic extraction based on signal quality control comprises the steps of performing quality control from a signal layer, and extracting frequency domain CSI information and time domain PDP information; establishing a multi-dimensional characteristic offline position fingerprint database based on time domain and frequency domain joint characteristics, wherein the fingerprint establishment comprises joint frequency domain CSI information and time domain PDP information; the robust fingerprint positioning based on ranging enhancement comprises the steps of constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by utilizing a multi-dimensional characteristic offline position fingerprint library, and constraining the fingerprint positioning result by utilizing a first-path energy ranging result to finally obtain the robust fingerprint positioning result. The positioning technical solution provided by the invention improves the accuracy and stability of the indoor positioning result.
Description
Technical Field
The invention relates to the technical field of indoor positioning, in particular to a positioning method and a positioning system based on signal quality control and characteristic fingerprint enhancement.
Background
With the progress of science and technology and the development of economy, the indoor positioning technology is more and more widely concerned. The indoor positioning technology is one of core technologies applied to everything interconnection, artificial intelligence and future ultra-intelligence (robots and human beings), and plays a great role in public safety services (such as emergency medical treatment, emergency positioning and emergency alarm service), intelligent warehousing, precise marketing, mobile health, virtual reality games, human social interaction and the like.
In an indoor environment, GNSS (global navigation satellite system) signals cannot be effectively received and used due to a severe multipath phenomenon, providing a location service to a user. The existing indoor positioning technology mostly uses various opportunity signals or multisource sensor information, and obtains the position information of indoor users by different methods. The existing indoor positioning technology based on wireless signals mainly comprises two methods of geometric intersection and fingerprint positioning:
(1) in the geometric intersection indoor positioning technology based on single distance measurement or angle measurement, stable distance and angle estimation results are difficult to obtain due to serious multipath phenomena caused by indoor environment and daily activities of human beings, and the precision and stability of an indoor positioning system are seriously influenced. Meanwhile, because more than three line-of-sight signals are difficult to receive simultaneously in an indoor environment, the deployment cost and the later maintenance cost of the positioning system are increased by additionally deploying too many base stations, and the popularization and the application of the technology are hindered.
(2) The indoor positioning technology based on the signal fingerprint is the most widely applied indoor positioning method at present because the influence of the multipath phenomenon does not need to be considered and the positioning precision is higher in a specific scene. In particular, positioning technologies based on signal CSI fingerprints have attracted much attention in recent years due to their obvious and relatively stable fingerprint characteristics. However, positioning techniques based on signal CSI fingerprints still face many challenges. First, fingerprint positioning is a positioning method that relies on matching of fingerprint information associated with a location in an indoor environment to achieve a positioning effect. When the indoor environment topology changes and the crowd activity changes, the fingerprint characteristics of the signals are affected. Therefore, when the fingerprint positioning system is used in a complicated indoor environment of a person, the change of the fingerprint characteristics of the indoor signal can cause a serious mismatching phenomenon of the positioning system, and the precision and the stability of the indoor positioning system are influenced. Secondly, the fingerprint positioning technology still has a certain demand for the number of indoor base stations. Generally, the more base station signals can be received, the more fingerprint features can be acquired, and the higher the accuracy of the positioning system is. How to realize the high-precision positioning effect by means of a small number of base station signals in an indoor environment is also a great challenge of fingerprint positioning.
In summary, the existing indoor positioning system is affected by the indoor environment, the crowd activity and the limitation of the number of base stations, so that the accuracy and stability of the system are difficult to guarantee, and a stable high-accuracy position service is provided for users. How to solve the problem is a hotspot of scientific research at present and is also a difficult point in industrial application. A perfect signal quality evaluation system can effectively screen high-quality data and improve the precision and stability of the indoor positioning system.
Aiming at the research difficulty and pain point, the technology provides a distance measurement and positioning method and system based on signal quality evaluation, and the accuracy and stability of indoor positioning are respectively improved through the following three aspects:
(1) by evaluating the quality of the received signal, the signals seriously affected by multipath fading and scattering are filtered, and the received signal with high signal-to-noise ratio is extracted. The signal with high signal-to-noise ratio is used for extracting the power of the first path, so that the reliability of the indoor positioning system is improved;
(2) the fingerprint positioning database is constructed based on the combination of signal quality control and time domain and frequency domain characteristics of signals, so that the fingerprint characteristic dimension and accuracy in the database are improved, and a high-precision indoor positioning effect is realized;
(3) based on signal quality control, the accuracy of fingerprint positioning is improved to a certain extent by using the ranging information of the line-of-sight signal, the condition of mismatching of fingerprint positioning is restrained, and the stability of the positioning method is improved.
Related terms:
CSI (Channel State Information);
PDP (Power Delay Profile);
RSSI (Received Signal Strength Index);
S-QoS (Signal Quality of Service);
SNR (Signal Noise Ratio).
Disclosure of Invention
The main problems of the prior art are as follows:
in the related technical scheme aiming at the fingerprint positioning technology, although some indoor positioning methods based on signal states are used, the stability or diversity of fingerprint characteristics in a fingerprint database is improved by methods such as a filtering algorithm, multiple antennas or multiple frequencies, and the like, and the precision of fingerprint positioning can be improved to a certain extent. However, due to the factors of the fingerprint positioning technology, the stability of the fingerprint positioning system in a complicated and varied indoor environment can not be guaranteed. According to the scheme, the accuracy of the data in the fingerprint database is improved through a signal quality control method. Meanwhile, the time-frequency characteristics are combined to construct a fingerprint database, so that the dimensionality of the fingerprint characteristics in the database is improved, and the fingerprint positioning matching precision can be effectively improved. A signal quality control based sight distance signal ranging enhanced fingerprint positioning method measures the distance between a base station and a user under the condition of sight distance to carry out real-time constraint on a fingerprint positioning result. The method not only can effectively improve the precision of the fingerprint positioning method, but also can effectively improve the stability of fingerprint positioning in a complex scene of personnel.
At present, according to the related technical scheme of the geometric intersection positioning technology, the precision of the indoor positioning system can be improved through methods such as multi-antenna measurement or error correction. However, these methods add additional cost to the system and make it difficult to make it widely applicable. The trilateral positioning method needs a plurality of sight distance signals to be intersected and positioned, and serious non-sight distance signals and multipath phenomena can be generated due to the interference of daily activities of human beings, so that the precision and the stability of the system are influenced. The scheme is an original fingerprint positioning method enhanced by the line-of-sight signal ranging of quality control. The method is based on a fingerprint positioning technology, and establishes a high-precision stable fingerprint characteristic database by combining signal time-frequency characteristics, so that enough fingerprint data can be collected for accurate matching positioning even if only one base station exists in an indoor scene. Meanwhile, the ranging precision and stability of the wireless signals can be improved through a ranging scheme of quality control, and when the line-of-sight signals can be received, the motion state of the user is restrained by measuring the distance between the user and the base station, so that the precision and stability of fingerprint positioning are enhanced.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
a positioning method based on signal quality control and characteristic fingerprint enhancement comprises the following steps,
and 3, based on ranging enhanced robust fingerprint positioning, constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by using the multi-dimensional characteristic offline position fingerprint library obtained in the step 2, and constraining the fingerprint positioning result by using the first-path energy ranging result to finally obtain a robust fingerprint positioning result.
Furthermore, the implementation of step 1 is as follows,
step 1.1, evaluating signal quality, which comprises demodulating and channel estimating wireless signals acquired by a receiver which supports synchronous signal acquisition to obtain an estimated vector H of CSI and calculating SNR;
step 1.2, controlling signal quality, including detecting and filtering abnormal data values according to the evaluation result, and further filtering CSI;
step 1.3, extracting frequency domain information, including calculating CSI amplitude according to the filtering result of the step 1.2;
and step 1.4, extracting time domain information, including calculating and analyzing the power delay distribution (PDP) of a channel.
And when the signal quality is controlled, recording the serial number of the position of the abnormal value of the current data by using a 3-Sigma rule, deleting the serial number data corresponding to the original CSI vector H, and denoising and smoothing by adopting a Hampel filtering method.
Furthermore, step 2 is implemented as follows,
step 2.1, performing feature normalization processing, namely respectively performing normalization processing on frequency domain CSI feature information and time domain PDP feature information of each subcarrier at the same position before combination;
and 2.2, combining the features to construct a fingerprint database, wherein the two features normalized in the step 2.1 are combined, and the fingerprint feature vector is constructed after the time domain PDP information is added to the frequency domain CSI information by adopting the weight of 1: 1.
Furthermore, step 3 is implemented as follows,
step 3.1, extracting the energy of the first path, including extracting the power of the first path of the signal according to the time domain PDP extraction result and the direct path which arrives at the first and the signal energy is relatively high, and calculating the energy EDP of the first path;
step 3.2, model distance inversion, including extracting direct path energy EDP according to time domain multipath PDP, modeling g (E) of direct path energy along with distance propagation loss relation of signal in indoor space 0 Gamma) to construct a terminal to receive direct path energy E d Environment factor gamma and signal propagation distance d R The relation between the two components is shown in the specification,
where g (-) is an indoor propagation loss model function, E 0 For the direct path energy received by the receiver at 1 meter in the current environment, E d The environment factor gamma reflects the current environment state for the direct path energy received by the receiver at the current environment test position;
step 3.3, fingerprint positioning, namely, establishing online test position fingerprint information in the same combined characteristic mode in an online stage by utilizing the multidimensional characteristic offline position fingerprint database established in the step 2, and realizing combined characteristic matching based on S-QoS by adopting a back propagation neural network algorithm to obtain an initial fingerprint positioning result L;
step 3.4, distance constraint enhanced positioning, which comprises the step of calculating the distance d between the base station and the receiver by utilizing the position information of the base station and the initial fingerprint positioning result L L According to d L And step 3.2 model distance inversion result d R Establishing distance-assisted fingerprint positioning relation model
Using relative distance error Δ d ═ d R -d L I update the distance d between the base station and the receiver L Finally over a distance d L And the constraint threshold delta is used for constraining the fingerprint positioning result L, so that the ranging enhanced stable fingerprint positioning is realized.
In another aspect, the present invention provides a positioning system based on signal quality control and feature fingerprint enhancement, which is used to implement a positioning method based on signal quality control and feature fingerprint enhancement as described above.
And, including the following modules,
a first module, configured to perform feature extraction based on signal quality control, including performing quality control from a signal level, and extracting frequency domain CSI information and time domain PDP information;
the second module is used for establishing a fingerprint based on the joint characteristics of the time domain and the frequency domain, and comprises the steps of combining the frequency domain CSI information and the time domain PDP information extracted by the first module to establish a multidimensional characteristic offline position fingerprint database;
and the third module is used for ranging-enhancement-based robust fingerprint positioning, and comprises the steps of constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by utilizing the multi-dimensional characteristic offline position fingerprint library obtained by the second module, and constraining the fingerprint positioning result by utilizing the first-path energy ranging result to finally obtain the robust fingerprint positioning result.
Alternatively, the system comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the positioning method based on signal quality control and characteristic fingerprint enhancement.
Alternatively, a readable storage medium is included, on which a computer program is stored, which, when executed, implements a signal quality control and feature fingerprint enhancement based positioning method as described above.
The invention provides an innovative method of an indoor positioning technology based on signal quality control (S-QoS) feature extraction, time domain and frequency domain signal feature fingerprint construction and distance constraint auxiliary enhancement, and the accuracy and the stability of an indoor positioning system are effectively improved. The method is mainly suitable for indoor positioning application scenes by utilizing multi-carrier signals (5G NR, 4G LTE, WiFi and the like). At present, received energy fluctuation of received signals caused by complex environment space topological structure in indoor positioning is large, indoor fingerprint positioning error based on multi-carrier signals is about 2-5 meters, and positioning results with high accuracy and high stability are generally difficult to obtain. Aiming at the problem, the invention provides an innovative solution of an indoor positioning technology based on signal quality control, time-frequency signal characteristic fingerprints and distance constraint auxiliary enhancement. The signal quality control technology solves the problem of large fluctuation of original signals, the time-frequency signal characteristic fingerprint improves indoor positioning accuracy, and the distance constraint auxiliary enhancement reduces positioning variance. The positioning error in a typical indoor scene is verified to be less than 2 meters (68% accuracy) by actual measurement. In general, the positioning technical solution provided by the present invention improves the accuracy and stability of the indoor positioning result.
The invention proposes the following innovations:
(1) feature processing method based on signal quality control
The traditional RSSI-based fingerprinting method does not process data from the signal layer side; the innovation point carries out quality evaluation on the signal based on the SNR index, and carries out filtering processing on the signal to obtain a signal with small error.
(2) Fingerprint establishing method based on time domain and frequency domain combined characteristics
The traditional RSSI-based fingerprint method is only based on energy single-dimensional information; the time domain signal can only reflect the distance propagation characteristic (time delay), the frequency domain signal can only reflect the channel state characteristic (carrier wave characteristic), and the innovation point combines the time domain signal and the frequency domain signal, so that the diversity of fingerprint positioning characteristics can be improved, and the phenomenon of mismatching caused by single characteristics can be resisted.
(3) Robust fingerprint positioning method based on ranging enhancement
The traditional RSSI-based fingerprint method only realizes positioning based on a fingerprint feature matching algorithm; the innovation point carries out distance measurement and fingerprint enhancement positioning on the first path energy extracted through S-QoS (quality of service), and further improves the stability of online positioning.
The scheme of the invention is simple and convenient to implement, has strong practicability, solves the problems of low practicability and inconvenient practical application of the related technology, can improve the user experience, and has important market value.
Drawings
Fig. 1 is a schematic diagram illustrating an embodiment of the present invention, wherein fig. 1(a) illustrates a positioning accuracy technical effect of the present invention, and fig. 1(b) illustrates a positioning stability technical effect of the present invention;
FIG. 2 is a flow chart of an embodiment of the present invention;
FIG. 3 is a diagram illustrating the detection of outliers deleted by Sigma rule according to example 3 of the present invention;
FIG. 4 is a schematic diagram illustrating comparison of frequency domain CSI amplitude effects based on signal quality control according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of frequency domain CSI amplitude characteristics according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating time-domain PDP features according to an embodiment of the present invention;
FIG. 7 is a flowchart of fingerprint establishment and comparison based on the joint characteristics of time domain and frequency domain of a single base station according to an embodiment of the present invention;
FIG. 8 is a flowchart of an embodiment of robust fingerprint location based on ranging enhancement;
FIG. 9 is a schematic diagram of direct path energy extraction according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a distance constraint enhanced positioning principle according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is specifically described below with reference to the accompanying drawings and examples.
The invention provides a positioning method based on signal quality control and characteristic fingerprint enhancement, which has the following technical effects through experiments:
(1) the positioning accuracy is improved:
(2) The positioning stability is improved:
An embodiment provides a positioning method based on signal quality control and feature fingerprint enhancement, a general flow is shown in fig. 2, and the method includes the following steps:
step 1: feature extraction based on signal quality control
In the traditional RSSI fingerprint positioning, only the data layer surface is used for denoising and filtering signals, the quality control is carried out on the signal layer surface by the technology, and the frequency domain CSI information and the time domain PDP information are extracted. The method comprises the following substeps:
(1) and (3) signal quality evaluation:
demodulating and channel estimating the wireless signal acquired by the receiver which supports the acquisition of the synchronous signal to obtain an estimation vector H of CSI:
wherein Y is a receiver received data vector, X is a pilot vector, and H i ＝|H i |exp{j∠H i }，|H i I and H i Respectively, the amplitude and phase of the ith subcarrier, j represents the imaginary part of the complex number, and exp { } is an exponential function.
Based on the idea of performing signal quality control on the amplitude of H, SNR is introduced into a signal quality evaluation index for the first time, which is an important index for measuring the influence degree of noise on a signal and can truly reflect the fading condition of each subcarrier of a channel, and the specific calculation method is as follows:
wherein, P s To receive signal power, P n Is the noise power.
The next sub-step will filter H using SNR as an evaluation index.
(2) Signal quality control:
and detecting and filtering abnormal data values according to the evaluation result, and further filtering the CSI. In this embodiment, the sequence number of the position where the abnormal value of the current data is located is deleted and recorded by using a 3-Sigma rule (laiida criterion), the sequence number data corresponding to the original CSI vector H is deleted, and a Hampel filtering method is adopted to perform denoising smoothing. The specific process comprises the following steps:
3-Sigma rule detection of deletion outliers: the index number of the position where the SNR time series abnormal value of each subcarrier is located is determined according to the 3-Sigma rule (mean μ and 3 times standard deviation σ threshold), and the index number is used to correspondingly delete the data on each subcarrier time series of the original CSI, which is shown in fig. 3.
Hampel filtering: and (4) removing the CSI data after the abnormal value is removed by utilizing the step (i), and denoising and smoothing the time series data on each subcarrier of the CSI by adopting a Hampel filtering algorithm.
And comparing amplitudes and standard deviations of the sub-carriers of the CSI before and after signal quality control. This step effectively reduces the fluctuation of the original signal data, obtains a truer and more stable signal, and improves the stability by about 1.2 times, as shown in fig. 4.
(3) Extracting frequency domain information:
the CSI amplitude is calculated from the filtering result of the substep (2), and the frequency domain CSI amplitude characteristics before and after signal quality control are as shown in fig. 5.
(4) Extracting time domain information:
calculating and analyzing the power delay distribution (PDP) of the channel, wherein the specific calculation method of the PDP is as follows:
wherein the time domain H (τ; t) is the result of the inverse frequency domain CSI vector H inverse Fourier transform (IFFT), i.e.
For the inverse Fourier transform operator, beta r (t) is the path gain, δ (·) is the impulse function, τ r For the delay of the r-th path signal propagation, τ is the delay variable and t is the time variable. The time domain PDP characteristics are shown in fig. 6.
Step 2: fingerprint establishment based on time domain and frequency domain joint characteristics
In order to improve the positioning accuracy, the technology expands the single-dimensional features of the traditional fingerprint positioning to multi-dimensional features, and in the step, the frequency domain CSI information and the time domain PDP information extracted in the step 1 are combined to construct a multi-dimensional feature offline position fingerprint database, as shown in FIG. 7. The method comprises the following specific substeps:
(1) and (3) feature normalization processing:
because the frequency domain CSI characteristic information and the time domain PDP characteristic information have different dimensions, the frequency domain CSI characteristic information and the time domain PDP characteristic information of each subcarrier at the same position are respectively subjected to normalization processing before combination, and a max-min normalization method is adopted to perform linear transformation on original data, so that a result value is mapped between 0 and 1. The transfer function is as follows:
wherein x is the original data, min is the minimum value of the characteristic vector, max is the maximum value of the characteristic vector, x * Is normalized data.
(2) And (3) combining the features to construct a fingerprint library:
combining the two features normalized in the substep (1), and adding time domain PDP information (assuming dimension 5) to the frequency domain CSI information (assuming dimension 60) by using a 1:1 weight, a 1 × 65 fingerprint feature vector can be constructed, as shown in fig. 7, assuming that there are N fingerprints at positions in the position fingerprint library:
And step 3: robust fingerprint positioning based on ranging enhancement
The method comprises the steps of adding distance constraint on the basis of traditional fingerprint positioning, acquiring an unknown position X by a receiver, performing signal quality control, obtaining an online fingerprint information vector combining a time domain PDP and a frequency domain CSI in the same combined characteristic mode as the steps 1 and 2, and recording the online characteristic vector at the ith moment of the unknown position X as the online characteristic vector
And (3) calculating a fingerprint positioning result corresponding to the online fingerprint information vector by using the time domain PDP, the frequency domain CSI fingerprint database and the traditional feature matching algorithm in the step (2), and constraining the fingerprint positioning result by using the first-path energy ranging result to improve the positioning stability and finally obtain a stable fingerprint positioning result, wherein the flow is shown in figure 8. The method comprises the following specific substeps:
(1) extracting energy of a first path:
according to the time domain PDP extraction result in step 1, the direct path (primary path) power of the signal is further extracted according to the basic idea that the direct path arrives first and the signal energy is relatively high, and the primary path energy EDP is calculated, and an example of the primary path energy extraction is shown in fig. 9.
(2) And (3) model distance inversion:
extracting direct path Energy (EDP) according to the time domain multipath PDP in the step 2, and modeling g (E) of the direct path energy of the signal in the indoor space along with the distance propagation loss relation 0 Gamma) to construct a terminal to receive direct path energy E d Environment factor gamma and signal propagation distance d R The relation between:
where g (-) is an indoor propagation loss model function, E 0 For the direct path energy received by the receiver at 1 meter in the current environment, E d The environmental factor gamma reflects the current environmental state for the direct path energy received by the receiver at the current environmental test location. In the present example, E 0 And gamma as unknown parameters, using a plurality of known different distances d and corresponding E in the model solution process d The distance inversion model in the current environment can be obtained by adopting a least square algorithm, and the distance inversion model can be used for obtaining the energy E of the acquired direct path at the unknown point according to the acquired direct path energy d Calculating the distance d between the receiver and the base station R Thus making necessary preparation for locating the distance constraint for subsequent fingerprints.
(3) Traditional fingerprint positioning:
and (3) acquiring an online fingerprint information vector of the time domain PDP and the frequency domain CSI in the online stage by using the offline stage time domain and frequency domain combined characteristic fingerprint library information established in the step (2) in the same combined characteristic mode as the steps (1) and (2), and then realizing combined characteristic matching based on S-QoS by using a back propagation neural network algorithm to obtain an initial positioning result L. The back propagation neural network algorithm is the prior art, and the details of the invention are not repeated.
(4) Distance constraint enhanced positioning:
using base station location information L BS And (3) calculating the distance d between the base station and the receiver according to the traditional fingerprint positioning result L L ＝s(L BS L), according to d L And (2) the model distance inversion result d R Establishing distance-assisted fingerprint positioning relation model
Using relative distance error Δ d ═ d R -d L I update the distance d between the base station and the receiver L Finally over a distance d L And a constraint threshold delta is used for constraining the fingerprint positioning result L to realize ranging enhancement stable fingerprint positioning, and a mathematical model is as follows:
wherein H CSI And P EDP As a fingerprint location feature, L XY And f (-) is a fingerprint position label, f (-) is a fingerprint positioning matching algorithm operator, s (-) is a distance calculation function, and u (-) is a positioning result updating optimization model. As shown in fig. 10, at distance constraint d R The original fingerprint positioning result L is limited to a smaller range, thereby obtaining a more stable positioning result L' with less fluctuation.
In specific implementation, a person skilled in the art can implement the automatic operation process by using a computer software technology, and a system device for implementing the method, such as a computer-readable storage medium storing a corresponding computer program according to the technical solution of the present invention and a computer device including a corresponding computer program for operating the computer program, should also be within the scope of the present invention.
In some possible embodiments, a signal quality control and feature fingerprint enhancement based positioning system is provided, comprising the following modules,
a first module, configured to perform feature extraction based on signal quality control, including performing quality control from a signal level, and extracting frequency domain CSI information and time domain PDP information;
the second module is used for establishing a fingerprint based on the time domain and frequency domain combined characteristics, and comprises frequency domain CSI information and time domain PDP information extracted by the first module in a combined manner to establish a multidimensional characteristic offline position fingerprint database;
and the third module is used for ranging-enhancement-based robust fingerprint positioning, and comprises the steps of constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by utilizing the multi-dimensional characteristic offline position fingerprint library obtained by the second module, and constraining the fingerprint positioning result by utilizing the first-path energy ranging result to finally obtain the robust fingerprint positioning result.
In some possible embodiments, a positioning system based on signal quality control and feature fingerprint enhancement is provided, which includes a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute a positioning method based on signal quality control and feature fingerprint enhancement as described above.
In some possible embodiments, a positioning system based on signal quality control and feature fingerprint enhancement is provided, which includes a readable storage medium, on which a computer program is stored, and when the computer program is executed, the positioning system based on signal quality control and feature fingerprint enhancement implements a positioning method based on signal quality control and feature fingerprint enhancement as described above.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (7)
1. A positioning method based on signal quality control and characteristic fingerprint enhancement is characterized in that: comprises the following steps of (a) carrying out,
step 1, extracting characteristics based on signal quality control, including quality control from a signal level and extracting frequency domain CSI information and time domain PDP information;
the implementation of step 1 is as follows,
step 1.1, evaluating signal quality, which comprises demodulating and channel estimating wireless signals acquired by a receiver which supports synchronous signal acquisition to obtain an estimated vector H of CSI and calculating SNR;
wherein the content of the first and second substances,
y is a data vector received by the receiver, and X is a pilot vector;
step 1.2, controlling signal quality, including detecting and filtering abnormal data values according to the evaluation result, and further filtering CSI;
step 1.3, extracting frequency domain information, including calculating CSI amplitude according to the filtering result of the step 1.2;
step 1.4, extracting time domain information, including calculating and analyzing the power delay distribution PDP of a channel;
step 2, establishing a multi-dimensional characteristic off-line position fingerprint database based on the time domain and frequency domain combined characteristic fingerprint, wherein the fingerprint establishment comprises combining the frequency domain CSI information and the time domain PDP information extracted in the step 1;
step 3, based on ranging enhanced robust fingerprint positioning, the method comprises the steps of constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by utilizing the multi-dimensional characteristic offline position fingerprint library obtained in the step 2, and constraining the fingerprint positioning result by using a first-path energy ranging result to finally obtain a robust fingerprint positioning result;
the step 3 is realized as follows,
step 3.1, extracting the energy of the first path, including extracting the power of the first path of the signal according to the time domain PDP extraction result and the direct path which arrives at the first and the signal energy is relatively high, and calculating the energy EDP of the first path;
step 3.2, model distance inversion, including extracting the primary path energy EDP according to the time domain multipath PDP, modeling g (E) of the direct path energy of the signal in the indoor space along with the distance propagation loss relation 0 Gamma) to construct a terminal to receive direct path energy E d Environment factor gamma and signal propagation distance d R The relation between the two components is shown in the specification,
where g (-) is an indoor propagation loss model function, E 0 For the receiver receiving at 1 meter in the current environmentEnergy to reach the diameter, E d The environment factor gamma reflects the current environment state for the direct path energy received by the receiver at the current environment test position;
step 3.3, fingerprint positioning, namely, establishing online test position fingerprint information in the same combined characteristic mode in an online stage by utilizing the multidimensional characteristic offline position fingerprint database established in the step 2, and realizing combined characteristic matching based on S-QoS by adopting a back propagation neural network algorithm to obtain an initial fingerprint positioning result L;
step 3.4, distance constraint enhanced positioning comprises the step of calculating the distance d between the base station and the receiver by utilizing the position information of the base station and the initial fingerprint positioning result L L According to d L And step 3.2 model distance inversion result d R Establishing distance-assisted fingerprint positioning relation model
Using relative distance error Δ d ═ d R -d L I update the distance d between the base station and the receiver L Finally over a distance d L And the constraint threshold delta is used for constraining the fingerprint positioning result L, so that the ranging enhanced stable fingerprint positioning is realized.
2. The signal quality control and characteristic fingerprint enhancement based positioning method according to claim 1, characterized in that: and during signal quality control, recording the serial number of the position of the abnormal value of the current data by using a 3-Sigma rule, deleting the serial number data corresponding to the original CSI vector H, and denoising and smoothing by adopting a Hampel filtering method.
3. The signal quality control and characteristic fingerprint enhancement based positioning method according to claim 1, characterized in that: the step 2 is realized as follows,
step 2.1, performing feature normalization processing, namely respectively performing normalization processing on frequency domain CSI feature information and time domain PDP feature information of each subcarrier at the same position before combination;
and 2.2, combining the features to construct a fingerprint database, wherein the two features normalized in the step 2.1 are combined, and the fingerprint feature vector is constructed after the time domain PDP information is added to the frequency domain CSI information by adopting the weight of 1: 1.
4. A positioning system based on signal quality control and feature fingerprint enhancement, characterized by: for implementing a signal quality control and characteristic fingerprint enhancement based positioning method according to any of claims 1-3.
5. The signal quality control and feature fingerprint enhancement based positioning system of claim 4, wherein: comprises the following modules which are used for realizing the functions of the system,
a first module, configured to perform feature extraction based on signal quality control, including performing quality control from a signal level, and extracting frequency domain CSI information and time domain PDP information;
the second module is used for establishing a fingerprint based on the time domain and frequency domain combined characteristics, and comprises frequency domain CSI information and time domain PDP information extracted by the first module in a combined manner to establish a multidimensional characteristic offline position fingerprint database;
and the third module is used for ranging-enhancement-based robust fingerprint positioning, and comprises the steps of constructing online test position fingerprint information in the same combined characteristic mode, calculating a fingerprint positioning result by utilizing the multi-dimensional characteristic offline position fingerprint library obtained by the second module, and constraining the fingerprint positioning result by utilizing the first-path energy ranging result to finally obtain the robust fingerprint positioning result.
6. The signal quality control and feature fingerprint enhancement based positioning system of claim 4, wherein: comprising a processor and a memory, the memory being adapted to store program instructions, the processor being adapted to invoke the stored instructions in the memory to perform a method of signal quality control and feature fingerprint enhancement based positioning according to any of claims 1-3.
7. The signal quality control and feature fingerprint enhancement based positioning system of claim 4, wherein: comprising a readable storage medium having stored thereon a computer program which, when executed, implements a signal quality control and feature fingerprint enhancement based positioning method according to any one of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110652675.4A CN113438731B (en) | 2021-06-11 | 2021-06-11 | Positioning method and system based on signal quality control and characteristic fingerprint enhancement |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110652675.4A CN113438731B (en) | 2021-06-11 | 2021-06-11 | Positioning method and system based on signal quality control and characteristic fingerprint enhancement |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113438731A CN113438731A (en) | 2021-09-24 |
| CN113438731B true CN113438731B (en) | 2022-08-05 |
Family
ID=77755748
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110652675.4A Active CN113438731B (en) | 2021-06-11 | 2021-06-11 | Positioning method and system based on signal quality control and characteristic fingerprint enhancement |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113438731B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114185003B (en) * | 2022-02-15 | 2022-05-10 | 武汉华康世纪医疗股份有限公司 | Indoor positioning method and system based on multi-source signal fusion |
| CN116184312B (en) * | 2022-12-22 | 2023-11-21 | 泰州雷德波达定位导航科技有限公司 | Indoor crowdsourcing fingerprint library construction method based on semantic Wi-Fi |
| CN116996993A (en) * | 2023-08-02 | 2023-11-03 | 泰州雷德波达定位导航科技有限公司 | Dynamic positioning method and system based on wireless signal channel state information |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105247384A (en) * | 2013-04-12 | 2016-01-13 | 惠普发展公司，有限责任合伙企业 | Distance determination of a mobile device |
| CN105678273A (en) * | 2016-01-14 | 2016-06-15 | 上海大学 | Initial point detection algorithm of transient signal in radio frequency fingerprint identification technology |
| CN109600711A (en) * | 2018-12-10 | 2019-04-09 | 西安交通大学 | A kind of indoor orientation method based on channel response frequency domain and airspace Combined Treatment |
| WO2020259055A1 (en) * | 2019-06-28 | 2020-12-30 | 华为技术有限公司 | Wireless positioning method, positioning apparatus, and network device |
| CN112261578A (en) * | 2020-10-21 | 2021-01-22 | 南京工业大学 | Indoor fingerprint positioning method based on mode filtering |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI722700B (en) * | 2019-12-06 | 2021-03-21 | 財團法人工業技術研究院 | Distance estimation device and method thereof and signal power calibration method |
-
2021
- 2021-06-11 CN CN202110652675.4A patent/CN113438731B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105247384A (en) * | 2013-04-12 | 2016-01-13 | 惠普发展公司，有限责任合伙企业 | Distance determination of a mobile device |
| CN105678273A (en) * | 2016-01-14 | 2016-06-15 | 上海大学 | Initial point detection algorithm of transient signal in radio frequency fingerprint identification technology |
| CN109600711A (en) * | 2018-12-10 | 2019-04-09 | 西安交通大学 | A kind of indoor orientation method based on channel response frequency domain and airspace Combined Treatment |
| WO2020259055A1 (en) * | 2019-06-28 | 2020-12-30 | 华为技术有限公司 | Wireless positioning method, positioning apparatus, and network device |
| CN112261578A (en) * | 2020-10-21 | 2021-01-22 | 南京工业大学 | Indoor fingerprint positioning method based on mode filtering |
Non-Patent Citations (2)
| Title |
|---|
| PDR+CSI指纹室内定位技术研究;王威;《中国优秀硕士学位论文全文数据库 信息科技辑》;20190915;全文 * |
| 基于信道状态信息的单节点高精度室内定位方法;李毅;《中国优秀硕士学位论文全文数据库 信息科技辑》;20180215;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113438731A (en) | 2021-09-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113438731B (en) | Positioning method and system based on signal quality control and characteristic fingerprint enhancement | |
| EP2798366B1 (en) | Method and system for localization | |
| Ferrand et al. | DNN-based localization from channel estimates: Feature design and experimental results | |
| Zhu et al. | BLS-location: A wireless fingerprint localization algorithm based on broad learning | |
| CN111556431B (en) | Fingerprint indoor positioning method based on signal subspace | |
| CN109490826B (en) | Ranging and position positioning method based on radio wave field intensity RSSI | |
| CN109901107A (en) | A kind of time difference positioning method, device, computer equipment and readable storage medium storing program for executing | |
| Zhang et al. | An efficient machine learning approach for indoor localization | |
| Alsindi et al. | An empirical evaluation of a probabilistic RF signature for WLAN location fingerprinting | |
| CN109640262B (en) | Positioning method, system, equipment and storage medium based on mixed fingerprints | |
| Ruan et al. | iPos-5G: Indoor positioning via commercial 5G NR CSI | |
| CN113595666B (en) | Channel prediction method and system of large-scale MIMO system based on time-frequency joint correlation | |
| CN103297924A (en) | Novel positioning fingerprint design method and indoor positioning system based on channel estimation | |
| WO2001050786A1 (en) | Method and system for creating a rf signature for a signature region in a wireless communication system | |
| CN110536245A (en) | A kind of indoor wireless positioning method and system based on deep learning | |
| CN107677989B (en) | A kind of indoor location localization method carrying out RSSI removal noise based on RSSI maximum value | |
| CN112040400B (en) | Single-site indoor fingerprint positioning method based on MIMO-CSI, storage medium and equipment | |
| WO2001050785A1 (en) | Method and system for comparing measured radio frequency signal propagation characteristics in a wireless communication system | |
| WO2016079656A1 (en) | Zero-calibration accurate rf-based localization system for realistic environments | |
| CN106992822A (en) | A kind of localization method of the blind node of wireless sensor network | |
| Zhang et al. | Radius based domain clustering for WiFi indoor positioning | |
| CN107071897B (en) | Wi-Fi indoor positioning method based on ring | |
| CN105704676A (en) | Method for improving fingerprint indoor positioning precision through employing signal time correlation | |
| CN111770528B (en) | Visual distance and non-visual distance identification method and device based on channel parameter extraction method | |
| Fan et al. | Single-site indoor fingerprint localization based on MIMO-CSI |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |