Indoor-outdoor seamless positioning system and method fusing pdr / gnss

Abstract

The application discloses a fusion PDR / GNSS indoor and outdoor seamless positioning system and method, and applies to the satellite navigation and dead reckoning technical field, and comprises a GNSS module, a PDR module, a joint step estimation module, a joint direction estimation module and a position updating module.The application effectively reduces the significant accumulated error of pedestrian dead reckoning (PDR) due to the low performance of MEMS devices with time growth, fuses PDR and GNSS, and thus optimal direction and step estimation are given.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of satellite navigation and dead reckoning, and in particular to an indoor and outdoor seamless positioning system and method fusing PDR / GNSS. BACKGROUND

[0002] With the development of smart phones, many traditional professional sensors used in high-precision navigation field are integrated into the smart phones, such as GNSS receivers, IMUs (gyroscopes and accelerometers), etc. However, the performance of low-cost devices is quite different from that of professional devices in performance indicators. For example, the zero offset of MEMS accelerometers is generally greater than 0.03 m / s 2 , the zero offset of MEMS gyroscopes is generally greater than 100° / h, and the GNSS positioning accuracy of a single-point positioning-based smart phone is usually about 10 m. Therefore, the traditional SINS (Strapdown Inertial Navigation System) is almost impossible to implement on MEMS IMUs, and researchers gradually shift their focus. Although the low accuracy of MEMS will cause integral errors in SINS, in some application scenarios such as pedestrian navigation and vehicle driving, MEMS sensors are also used to assist in attitude measurement, and the attitude change has certain regularity, so the integral errors caused by MEMS devices can be eliminated to a certain extent by designing corresponding algorithms, thus developing the research direction of PDR (Pedestrian Dead Reckoning) and VDR (Vehicle Dead Reckoning). Taking the traditional GNSS and INS integrated navigation as an example, this is a highly complementary system, and therefore it has achieved success in many application fields. However, on a smart phone, on the one hand, the performance of MEMS is insufficient to support INS, and on the other hand, due to the openness of the respective systems, it is difficult to achieve tighter coupling of the two systems. According to the depth of coupling, integrated navigation can be divided into three types: loose coupling at the level of positioning results, tight coupling at the level of observations, and deep coupling at the level of signal tracking. With the opening of the raw GNSS observations of Android phones in recent years, tight coupling of MEMS and low-cost GNSS is theoretically supported, but there are still great challenges in such research.

[0003] Because low-cost MEMS based on smart phone and GNSS still cannot realize GNSS / INS integrated navigation at present, the fusion of MEMS based PDR and GNSS is considered to be achievable. As mentioned above, the fusion based on PDR and low-cost GNSS can be loose coupling or tight coupling. The traditional method is a fusion algorithm framework based on 3D map assisted GNSS and PDR in urban environment, which sends the output step length and heading of PDR and the position and accuracy of 3D-GNSS into Kalman filter together, so as to obtain the fusion result, thus it is a loose coupling method. The observation of Kalman filter comes from 3D-GNSS, and the output of PDR is used for control input, because the trajectory of pedestrian has great uncertainty, it is difficult to describe with linear state transition equation, therefore, the real-time observation of PDR is used to update the state transition equation, but since PDR still has cumulative error, this design inevitably leads to the accumulation of error of the whole system over time, resulting in the final yaw. In the traditional method, the extended Kalman filter (EKF) is used to fuse PDR and GNSS, and the algorithm is directly based on the output information of MEMS sensor, so it can be regarded as a tight coupling algorithm. The algorithm uses the heading derived by GNSS to assist the heading estimation of MEMS gyroscope, so as to improve the heading estimation accuracy, but the serious noise problem of GNSS heading is not well solved, so the initial stage of the final trajectory output is seriously dependent on the heading of GNSS.

[0004] Therefore, to solve the above technical problems, the present application provides an indoor and outdoor seamless positioning system and method fusing PDR / GNSS. SUMMARY

[0005] Therefore, to solve the above technical problems, the present application provides an indoor and outdoor seamless positioning system and method fusing PDR / GNSS.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0007] An indoor and outdoor seamless positioning system fusing PDR / GNSS comprises:

[0008] a GNSS module, a PDR module, a joint step length estimation module, a joint heading estimation module and a position updating module;

[0009] The GNSS module sends GNSS step length estimation to the first input end of the joint step length estimation module;

[0010] The GNSS module sends the GNSS step length estimate to a first input of the joint step length estimation module;

[0011] The PDR module sends the PDR step length estimate to a second input of the joint step length estimation module;

[0012] The PDR module sends the PDR gait detection to a third input of the joint step length estimation module;

[0013] The PDR module sends the PDR heading estimate to a second input of the joint heading estimation module;

[0014] The joint step length estimation module sends joint step length estimation information to a first input of the position update module;

[0015] The joint heading estimation module sends joint heading estimation information to a second input of the position update module;

[0016] The position update module is configured to update position information based on the received joint step length estimation information and joint heading estimation information.

[0017] Optionally, the PDR module comprises an accelerometer, a gyroscope, a magnetometer, a step length estimation unit, a gait detection unit, and a heading estimation unit;

[0018] The accelerometer sends acceleration data to the step length estimation module, and the step length estimation module outputs the PDR step length estimate;

[0019] The accelerometer sends acceleration data to the gait detection module, and the gait detection module outputs the PDR gait detection;

[0020] The gyroscope and the magnetometer send detection data to the heading estimation unit, and the heading estimation unit outputs the PDR heading estimate.

[0021] Optionally, the GNSS module comprises a GNSS receiver, a coordinate conversion unit, and a GNSS estimation unit;

[0022] The GNSS receiver sends longitude and latitude information to the coordinate conversion unit, the coordinate conversion unit converts the longitude and latitude information into north-east sky coordinates, and sends the north-east sky coordinates to the GNSS estimation unit, and the GNSS estimation unit converts the north-east sky coordinates into GNSS step length estimate and GNSS heading estimate.

[0023] Optionally, a map display module is further included, connected to an output of the position update module, configured to receive the position result output by the position update module and display the position result on a map.

[0024] A PDR / GNSS fusion indoor and outdoor seamless positioning method, wherein an initial position of a pedestrian is provided by a GNSS module, and the method comprises the following steps:

[0025] Pedestrian initial position obtaining step: obtaining GNSS receiver positioning information and satellite information;

[0026] Fusion data obtaining step: obtaining PDR step length estimation and PDR heading estimation, GNSS step length estimation and GNSS heading estimation;

[0027] Joint step length estimation step: fusing PDR step length estimation and GNSS step length estimation through weighted calculation to obtain joint step length estimation information;

[0028] Joint heading estimation step: fusing PDR heading estimation and GNSS heading estimation to obtain joint heading estimation information;

[0029] Position updating step: iteratively updating pedestrian position according to joint step length estimation information and joint heading estimation information.

[0030] Optionally, in the fusion data obtaining step, the PDR step length estimation adopts a binary linear regression model with step frequency and acceleration variance as variables, and the expression is as follows:

[0031]

[0032] Wherein, f S is the step frequency, is the acceleration variance, and α and β are weight factors, and γ is a constant;

[0033] The PDR heading estimation adopts redundant information of the gyroscope and the magnetometer to obtain heading estimation.

[0034] Optionally, in the fusion data obtaining step, it further includes synchronizing PDR and GNSS output data, and the specific content is as follows:

[0035] Between the m and m+1 moments of GNSS, there are two PDR outputs, which are n+1 and n+2, and the corresponding {θ n+1 ,SL n+1} and {θ n+2 ,SL n+2} are obtained, and the output {θ m ,SL m} of one PDR obtained at the m moment of GNSS is defined, and the formula is as follows:

[0036]

[0037] Wherein, θ m is the PDR heading estimation at the m moment, SL m is the PDR step length estimation at the m moment, and C is an intermediate quantity.

[0038] Optionally, the specific content of the fusion data acquisition step of GNSS step length estimation and GNSS heading estimation is: using coordinate conversion method, the output of the GNSS receiver is first converted into ECEF XYZ coordinates, and then the obtained ECEF XYZ coordinates are converted into East-North-Up coordinates based on the initial position. Assuming that (E k ,N k ,U k ) and (E k+1 ,N k+1 ,U k+1 ) are the East-North-Up coordinates at k and k+1 time, the calculation formula of GNSS heading estimation and GNSS step length estimation is as follows:

[0039]

[0040]

[0041] is the GNSS heading estimation at k+1 time, is the GNSS step length estimation at k+1 time.

[0042] Optionally, the specific content of the joint heading estimation step is:

[0043] The PDR heading estimation and the GNSS heading estimation are fused, and the specific implementation is shown by the following formula:

[0044]

[0045] wherein, Θ k+1 is the joint heading estimation at k+1 time, is the PDR heading estimation at k+1 time, is the GNSS heading estimation at k+1 time, and p is a weighting coefficient in the range of [0, 1].

[0046] Optionally, the iterative update of the pedestrian position in the position update step is completed by the following formula,

[0047]

[0048] wherein, (x k+1 ,y k+1 ) represents the two-dimensional position coordinates of the pedestrian at iteration step k+1, SL k represents the step length at iteration step k, θ represents the heading at iteration step k, and k represents the iteration step number.

[0049] Compared with the prior art, the application provides an indoor and outdoor seamless positioning system and method fusing PDR / GNSS, which effectively reduces the significant accumulated error of pedestrian dead reckoning (PDR) due to the low performance of MEMS devices over time, fuses PDR and GNSS, and thus gives optimal heading and step length estimation. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only represent some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of the provided drawings.

[0051] Figure 1 FIG. 1 is a structural block diagram of the indoor and outdoor seamless positioning system fusing PDR / GNSS according to the present application.

[0052] Figure 2 FIG. 2 is a structural block diagram of the PDR module according to the present application.

[0053] Figure 3 FIG. 3 is a structural block diagram of the GNSS module according to the present application.

[0054] Figure 4 FIG. 4 is a structural block diagram of the joint step length estimation module according to the present application.

[0055] Figure 5 FIG. 5 is a structural block diagram of the joint heading estimation module according to the present application.

[0056] Figure 6 FIG. 6 is a working principle block diagram of the position updating unit according to the present application. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments only represent some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the scope of the present application.

[0058] With reference to the drawings shown in the accompanying drawings, Figure 1 The present application discloses an indoor and outdoor seamless positioning system fusing PDR / GNSS, which comprises:

[0059] a GNSS module, a PDR module, a joint step length estimation module, a joint heading estimation module, and a position updating module.

[0060] The GNSS module sends GNSS step length estimates to a first input of a joint step length estimation module;

[0061] The GNSS module sends GNSS heading estimates to a first input of a joint heading estimation module;

[0062] The PDR module sends PDR step length estimates to a second input of the joint step length estimation module;

[0063] The PDR module sends PDR gait detection to a third input of the joint step length estimation module;

[0064] The PDR module sends PDR heading estimates to a second input of the joint heading estimation module;

[0065] The joint step length estimation module sends joint step length estimation information to a first input of a position update module;

[0066] The joint heading estimation module sends joint heading estimation information to a second input of the position update module;

[0067] The position update module is configured to update position information based on the received joint step length estimation information and joint heading estimation information.

[0068] In one embodiment, the PDR module comprises an accelerometer, a gyroscope, a magnetometer, a step length estimation unit, a gait detection unit, and a heading estimation unit;

[0069] The accelerometer sends acceleration data to the step length estimation module, which outputs PDR step length estimates;

[0070] The accelerometer sends acceleration data to the gait detection module, which outputs PDR gait detection;

[0071] The gyroscope and the magnetometer send detection data to the heading estimation unit, which outputs PDR heading estimates.

[0072] In one embodiment, the PDR heading estimates are obtained as follows: first, the change in sensor attitude is obtained by integrating the gyroscope measurements, i.e. angular velocity, and in the case of known initial state, the attitude of the sensor in the subsequent state is recursively calculated; then the attitude of the sensor is directly solved by the components of the acceleration and the magnetic field measurements in the direction of gravity and the magnetic north. Therefore, sufficient measurements for solving the attitude can be obtained by the gyroscope and the magnetometer. In the attitude fusion, the observations of the two sensors are combined, and the pitch angle and the roll angle of the sensor are output by weighted fusion of the accelerometer and the gyroscope, and then the yaw angle of the sensor is output by weighted fusion of the magnetometer and the gyroscope.

[0073] In one embodiment, the GNSS module comprises: a GNSS receiver, a coordinate conversion unit and a GNSS estimation unit;

[0074] The GNSS receiver sends the longitude and latitude information to the coordinate conversion unit, the coordinate conversion unit converts the longitude and latitude information into the north-east sky coordinates, and sends the north-east sky coordinates to the GNSS estimation unit, and the GNSS estimation unit converts the north-east sky coordinates into the GNSS step estimation and the GNSS heading estimation.

[0075] In one embodiment, a map display module is further included, connected to the output end of the position updating module, for receiving the position result output by the position updating module and displaying the position result on a map.

[0076] The application further discloses an indoor and outdoor seamless positioning method fusing PDR / GNSS, wherein the initial position of the pedestrian is provided by the GNSS module, and the method comprises the following steps:

[0077] The initial position of the pedestrian is obtained by obtaining the positioning information and satellite information of the GNSS receiver, obtaining the positioning information, satellite information reported by the GNSS receiver, analyzing the protocol, and buffering the positioning information, satellite posture, satellite signal signal-to-noise ratio and satellite data validity.

[0078] The fusion data is obtained by obtaining the PDR step estimation and the PDR heading estimation, the GNSS step estimation and the GNSS heading estimation.

[0079] The joint step estimation is obtained by fusing the PDR step estimation and the GNSS step estimation through weighted calculation.

[0080] The joint heading estimation is obtained by fusing the PDR heading estimation and the GNSS heading estimation.

[0081] The position is updated according to the joint step estimation information and the joint heading estimation information.

[0082] In one embodiment, the specific implementation details and output of the PDR module are as follows: the algorithm generally comprises three steps: gait detection, step estimation and heading estimation. The 3-axis output of the accelerometer is generally used for detecting the occurrence of a step and estimating the step length, and the heading is generally given by the gyroscope or the magnetometer. Therefore, the heading and step length estimation of the kth step {θ, SL} are output after completing a gait detection.

[0083] Gait detection is mainly to detect the periodic signal generated by accelerometer when the pedestrian walks, so as to determine whether the pedestrian has stepped. First, the acceleration data is preprocessed, and the noise in the original data is effectively reduced by setting the cutoff frequency of the low-pass filter to 3Hz, and then the dynamic threshold zero-crossing detection method is adopted, and the finite state machine is used to control the conversion between walking and non-walking states.

[0084] Referring to Figure 2 In the fusion data acquisition step, the PDR step length estimation adopts a binary linear regression model with step frequency and acceleration variance as variables, and its expression is as follows:

[0085]

[0086] Where f S is the step frequency, is the acceleration variance, and a and β are weight factors, and γ is a constant;

[0087] The PDR heading estimation adopts the redundant information of the gyroscope and the magnetometer to obtain the heading estimation.

[0088] The heading estimation in the PDR module usually adopts the gyroscope, the magnetometer or the method of combining the two. Since the gyroscope will produce cumulative error when integrated, and the magnetometer is easily disturbed by the surrounding magnetic field, the two have obvious complementary characteristics. The heading estimation adopted in this paper combines the gyroscope and the magnetometer, and obtains the optimal estimated heading by using the redundant information of the two. Therefore, the final output of the PDR module is gait detection, step length estimation and heading estimation.

[0089] In one specific embodiment, it also includes synchronizing the PDR with the GNSS output data. In the fusion system, the output of the PDR module is not timed, while the GNSS module is fixed period output positioning result, usually with an update rate of 1Hz. Therefore, in order to be able to real-time fuse the data of the two, it is necessary to make the output of the two systems consistent. The data of the PDR module is changed into timed output. The specific content is:

[0090] Between the m and m+1 moments of GNSS, there are two PDR outputs, which are n+1 and n+2, corresponding to get {θ n+1 ,SL n+1} and {θ n+2 ,SL n+2}, define the output of a PDR at the m moment of GNSS as {θ m ,SL m}, and the formula is as follows:

[0091]

[0092] Where θm For PDR heading estimation at time m, SL m Let C be the PDR step size estimate at time m, and C be an intermediate quantity.

[0093] Simultaneously, after synchronization processing, the PDR module outputs synchronized heading and step size {θ} with the GNSS module at a fixed frequency. PDR ,SL PDR}

[0094] In one specific embodiment, refer to Figure 3 As shown, the specific content of GNSS step size estimation and GNSS heading estimation in the data fusion acquisition step is as follows: Using a coordinate transformation method, the latitude, longitude, and altitude information output by the GNSS receiver is first converted into ECEF XYZ coordinates. Then, based on the initial position, the obtained ECEF XYZ coordinates are converted into northeast-sky coordinates. On this two-dimensional plane, heading and step size similar to those in a PDR system can be defined; assuming (E... k N k U k ) and (E k+1 N k+1 U k+1 Let ) be the northeast celestial coordinates at times k and k+1. Then, the formulas for calculating GNSS heading estimation and GNSS step size estimation are as follows:

[0095]

[0096]

[0097] For the GNSS heading estimation at time k+1, This is the GNSS step size estimate at time k+1.

[0098] It should be noted that the definition of GNSS heading is the same as that of PDR, which is the angle between the vectors of the two positioning results and the due north direction. Note that the heading value range in this formula is (-π, +π).

[0099] In one specific embodiment, refer to Figure 4 and Figure 5 The PDR heading estimate and GNSS heading estimate are fed into the joint heading estimation module, which combines the PDR step size estimate and GNSS step size estimate into a joint heading estimation module. The purpose of the joint heading estimation module is to fuse the PDR heading with accumulated error and the GNSS heading with random noise, thereby achieving the dual effect of reducing accumulated error and noise power. Its specific implementation is shown in the following equation:

[0100]

[0101]

[0102] wherein, is the heading estimate of the k+1th step, is the heading estimate of the kth step, is the PDR heading estimate at time k, M is the smoothing factor, which is generally selected from the range of 10-30,

[0103] Θ k+1 is the joint heading estimate of the k+1th step, is the PDR heading estimate of the k+1th step, is the GNSS heading estimate of the k+1th step, p is a weighting factor in the range of [0, 1].

[0104] The result of formula (6) is input into formula (5) to obtain the final joint heading estimate Similarly, the final joint step length estimate can be obtained Then, the final heading and step length estimates after fusion filtering are output as

[0105] In one specific embodiment, the iterative update of the pedestrian position in the position update step is completed by the following formula,

[0106]

[0107] wherein, (x k+1 ,y k+1 ) represents the two-dimensional position coordinates of the pedestrian at the k+1th iteration step, SL k represents the step length at the kth iteration step, θ represents the heading at the kth iteration step, and k represents the iteration step number.

[0108] In one specific embodiment, in order to measure the heading error of the two systems, the average cumulative heading error (MCHE) formula is used for calculation, and the formula is as follows:

[0109]

[0110] wherein, SYS can be GNSS or PDR; when k increases, the zero mean noise MCHE of GNSS tends to zero, and the cumulative error MCHE of PDR is divergent.

[0111] Then, the cumulative step length error (CSLE) is defined to measure the step length error characteristics of the two systems, and the formula is as follows:

[0112]

[0113] wherein, SYS can be GNSS or PDR.

[0114] The foregoing description of the disclosed embodiments is presented in the context of a progression of related embodiments, which together provide a description of the present application. Modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Accordingly, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A seamless indoor / outdoor positioning system integrating PDR / GNSS, characterized in that, include: GNSS module, PDR module, joint step size estimation module, joint heading estimation module, position update module; The GNSS module sends the GNSS step size estimate to the first input of the joint step size estimate module; The GNSS module sends the GNSS heading estimate to the first input of the joint heading estimate module; The PDR module sends the PDR step size estimate to the second input of the joint step size estimate module; The PDR module sends the PDR gait detection to the third input of the joint step length estimation module; The PDR module sends the PDR heading estimate to the second input of the joint heading estimate module; The joint step size estimation module sends the joint step size estimation information to the first input of the position update module; The joint heading estimation module sends the joint heading estimation information to the second input of the position update module; The position update module is used to update the position information based on the received joint step size estimation information and joint heading estimation information; The joint step size estimation module fuses the PDR step size estimation and the GNSS step size estimation through weighted calculation to obtain joint step size estimation information; The joint heading estimation module fuses the PDR heading estimate and the GNSS heading estimate to obtain joint heading estimation information; the specific implementation formula is as follows: in, This is the heading estimate for the (k+1)th step. Here, M is the heading estimate for the k-th step, and M is the smoothing factor, typically ranging from 10 to 30; Θ k+1 For the joint heading estimation at time k+1, For PDR heading estimation at time k+1, For the GNSS heading estimate at time k+1, p is a weighting coefficient in the range [0,1]. The result of formula (6) is input into formula (5) to obtain the final joint heading estimate.

2. A seamless indoor / outdoor positioning system integrating PDR / GNSS according to claim 1, characterized in that, The PDR module includes: accelerometer, gyroscope, magnetometer, step length estimation unit, gait detection unit, and heading estimation unit; The accelerometer sends acceleration data to the step size estimation module, which outputs the PDR step size estimate. Accelerometer acceleration data is sent to the gait detection module, and the gait detection module outputs PDR gait detection. The gyroscope and magnetometer send the detection data to the heading estimation unit, which outputs the PDR heading estimate.

3. A seamless indoor / outdoor positioning system integrating PDR / GNSS according to claim 1, characterized in that, The GNSS module includes: a GNSS receiver, a coordinate transformation unit, and a GNSS calculation unit; The GNSS receiver sends latitude, longitude, and altitude information to the coordinate transformation unit. The coordinate transformation unit converts the latitude, longitude, and altitude information into northeast-sky coordinates and sends the northeast-sky coordinates to the GNSS estimation unit. The GNSS estimation unit converts the northeast-sky coordinates into GNSS step size estimates and GNSS heading estimates.

4. A seamless indoor / outdoor positioning system integrating PDR / GNSS according to claim 1, characterized in that, It also includes a map display module, which is connected to the output of the location update module and is used to receive the location results output by the location update module and display them on the map.

5. A seamless indoor / outdoor positioning method integrating PDR / GNSS, characterized in that, The pedestrian's initial position is provided by the GNSS module, including the following steps: Steps for obtaining the initial location of pedestrians: Obtain GNSS receiver positioning information and satellite information; Data fusion acquisition steps: acquire PDR step size estimate and PDR heading estimate, GNSS step size estimate and GNSS heading estimate; Joint step size estimation steps: The PDR step size estimate and the GNSS step size estimate are fused through weighted calculation to obtain joint step size estimate information; Joint heading estimation steps: Fuse the PDR heading estimate and the GNSS heading estimate to obtain joint heading estimation information; Location update steps: Iteratively update the pedestrian's location based on the joint step size estimation information and the joint heading estimation information.

6. A seamless indoor / outdoor positioning method integrating PDR / GNSS according to claim 5, characterized in that, In the data fusion acquisition step, the PDR step size estimation adopts a binary linear regression model with step frequency and acceleration variance as variables, and its expression is as follows: Among them, f S It's step frequency. The variance of acceleration is α and β, which are weighting factors, and γ is a constant. PDR heading estimation uses redundant information from gyroscopes and magnetometers to obtain the heading estimate.

7. A seamless indoor / outdoor positioning method integrating PDR / GNSS according to claim 6, characterized in that, The data fusion acquisition step also includes synchronizing PDR and GNSS output data, specifically as follows: Between GNSS times m and m+1, there are two PDR outputs, n+1 and n+2, corresponding to {θ}. n+1 ,SL n+1 } and {θ n+2 ,SL n+2 }, defining the output {θ} of a PDR obtained at time m in GNSS. m ,SL m The formula is as follows: Where, θ m For PDR heading estimation at time m, SL m Let C be the PDR step size estimate at time m, and C be an intermediate quantity.

8. A seamless indoor / outdoor positioning method integrating PDR / GNSS according to claim 7, characterized in that, The specific content of GNSS step size estimation and GNSS heading estimation in the data fusion acquisition step is as follows: Using a coordinate transformation method, the latitude, longitude, and altitude information output by the GNSS receiver is first converted into ECEF XYZ coordinates. Then, based on the initial position, the obtained ECEF XYZ coordinates are converted into northeast-sky coordinates. The calculation formulas for GNSS heading estimation and GNSS step size estimation are as follows: in, For the GNSS heading estimation at time k+1, For the GNSS step size estimation at time k+1, (E k N k U k ) and (E k+1 N k+1 U k+1 ) represents the northeast celestial coordinates at times k and k+1.

9. A seamless indoor / outdoor positioning method integrating PDR / GNSS according to claim 8, characterized in that, The specific steps of the joint heading estimation process are as follows: The fusion of PDR heading estimation and GNSS heading estimation is specifically implemented as shown in the following formula: Where, Θ k+1 For the joint heading estimation at time k+1, For PDR heading estimation at time k+1, For the GNSS heading estimate at time k+1, p is a weighting coefficient in the range [0,1].

10. A seamless indoor / outdoor positioning method integrating PDR / GNSS according to claim 9, characterized in that, The iterative update of pedestrian positions in the location update step is accomplished by the following formula: Among them, (x k+1 ,y k+1 ) represents the two-dimensional position coordinates of the pedestrian when the iteration step is k+1, SL k θ represents the step size when the number of iterations is k, θ represents the heading when the number of iterations is k, and k represents the number of iterations.

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