A gravity sensing data processing method for mobile terminal

Abstract

The present invention relates to the field of comprehensive analysis and processing of gravity sensor data of mobile devices, and particularly to a method for processing gravity sensor data for a mobile terminal, including: obtaining gravity sensor combined data by using the gravity sensor data of the mobile terminal; establishing a three-dimensional unidirectional gravity sensor model according to the gravity sensor combined data; obtaining a gravity sensor data processing result by using the gravity sensor data and the three-dimensional unidirectional gravity sensor model. The concept of the three-dimensional unidirectional model is innovatively proposed. By means of the characteristic that gravity is vertically downward in terms of physical properties, subsequent feature comparison of the solution is carried out, and the cycle and rapid verification of the logic of the solution itself are realized.

Description

Technical Field

[0001] The present invention relates to the field of comprehensive analysis and processing of gravity sensor data of mobile devices, and particularly relates to a method for processing gravity sensor data for a mobile terminal. Background Art

[0002] When analyzing gravity sensor data, traditional methods often ignore the complexity of the three-dimensional space and only focus on the movement of the device in a single direction. Although they can provide quick solutions in some cases, they cannot comprehensively capture the complexity of the movement of objects in the real world. Due to the lack of comprehensive consideration of all movement dimensions in the three-dimensional space, this analysis process is prone to data distortion. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a method for processing gravity sensor data for a mobile terminal, which can quickly and accurately analyze the state of gravity sensor data of a mobile device by establishing a three-dimensional coordinate model of numerical values and corresponding features.

[0004] To achieve the above object, the present invention provides a method for processing gravity sensor data for a mobile terminal, including:

[0005] S1. Obtain gravity sensor combined data by using the gravity sensor data of the mobile terminal;

[0006] S2. Establish a three-dimensional unidirectional model of gravity induction according to the gravity sensor combined data;

[0007] S3. Obtain the processing result of gravity sensor data by using the gravity sensor data and the three-dimensional unidirectional model of gravity induction.

[0008] Preferably, the obtaining of gravity sensor combined data by using the gravity sensor data of the mobile terminal includes:

[0009] S1-1. Respectively obtain real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data based on the gravity sensor data;

[0010] S1-2. Respectively obtain the data features of the real-time gravitational acceleration data, the data features of the real-time gravity data, and the data features of the real-time rotation vector data according to the real-time gravitational acceleration data, the real-time gravity data, and the real-time rotation vector data;

[0011] S1-3. Use the real-time gravitational acceleration data, the real-time gravity data, the real-time rotation vector data, the data features of the real-time gravitational acceleration data, the data features of the real-time gravity data, and the data features of the real-time rotation vector data as the gravity sensor combined data.

[0012] Further, obtaining the data features of the real-time gravitational acceleration data, the real-time gravitational data, and the real-time rotation vector data respectively based on the real-time gravitational acceleration data, the real-time gravitational data, and the real-time rotation vector data includes:

[0013] S1-2-1. Using the corresponding moment of the real-time gravitational acceleration data as the standard data processing moment t;

[0014] S1-2-2. Respectively obtaining the gravitational acceleration data at the moment t - 1 and the gravitational acceleration data at the moment t + 1;

[0015] S1-2-3. Obtaining the change rate of the gravitational acceleration data as the first change rate according to the gravitational acceleration data at the moment t - 1 and the real-time gravitational acceleration data at the standard data processing moment t;

[0016] S1-2-4. Obtaining the change rate of the gravitational acceleration data as the second change rate according to the real-time gravitational acceleration data at the standard data processing moment t and the gravitational acceleration data at the moment t + 1;

[0017] S1-2-5. Using the first change rate and the second change rate as the data features of the real-time gravitational acceleration data;

[0018] S1-2-6. Respectively obtaining the real-time gravitational data at the moment t - 1 and the real-time gravitational data at the moment t + 1;

[0019] S1-2-7. Obtaining the change trend of the gravitational data as the first trend according to the real-time gravitational data at the moment t - 1 and the real-time gravitational data at the standard data processing moment t;

[0020] S1-2-8. Obtaining the change trend of the gravitational data as the second trend according to the real-time gravitational data at the standard data processing moment t and the real-time gravitational data at the moment t + 1;

[0021] S1-2-9. Using the first trend and the second trend as the data features of the real-time gravitational data;

[0022] S1-2-10. Respectively obtaining the real-time rotation vector data at the moment t - 1 and the real-time rotation vector data at the moment t + 1;

[0023] S1-2-11. Obtaining the relative change angle of the rotation vector data as the first relative change angle according to the real-time rotation vector data at the moment t - 1 and the real-time rotation vector data at the standard data processing moment t;

[0024] S1-2-12. Obtain the relative change angle of the rotation vector data by using the real-time rotation vector data at the standard data processing time t and the real-time rotation vector data at time t + 1 as the second relative change angle;

[0025] S1-2-13. Use the first relative change angle and the second relative change angle as the data features of the real-time rotation vector data.

[0026] Further, establishing a gravity induction three-dimensional one-way model based on the gravity induction combined data includes:

[0027] Establish a real-time motion three-dimensional model of gravity induction by using the real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data of the gravity induction combined data;

[0028] Establish a numerical change model of gravity induction by using the data features of the real-time gravitational acceleration data, the data features of the real-time gravity data, and the data features of the real-time rotation vector data;

[0029] Use the real-time motion three-dimensional model and the numerical change model of gravity induction as the gravity induction three-dimensional one-way model.

[0030] Further, establishing a real-time motion three-dimensional model of gravity induction by using the real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data of the gravity induction combined data includes:

[0031] Use the corresponding time sequence of the real-time gravitational acceleration data of the gravity induction combined data as the X-axis, the numerical change of the real-time gravity data of the gravity induction combined data as the Y-axis, and the corresponding motion direction of the real-time rotation vector data of the gravity induction combined data as the Z-axis to establish a basic motion three-dimensional coordinate system;

[0032] Establish a real-time three-dimensional vector of the gravity induction combined data according to the basic motion three-dimensional coordinate system by using the real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data of the gravity induction combined data;

[0033] Obtain the real-time three-dimensional vector corresponding to time t - 1 and the real-time three-dimensional vector corresponding to time t + 1 of the real-time three-dimensional vector of the gravity induction combined data respectively;

[0034] Obtain the real-time motion three-dimensional model of gravity induction by using the real-time three-dimensional vector at time t - 1, the real-time three-dimensional vector, and the real-time three-dimensional vector at time t + 1.

[0035] Further, establishing a numerical change model of gravity induction by using the data features of the real-time gravitational acceleration data, the data features of the real-time gravity data, and the data features of the real-time rotation vector data includes:

[0036] Establish a fixed Z-axis three-dimensional coordinate system for basic gravity sensing with the time series corresponding to the data characteristics of the real-time gravitational acceleration data as the X-axis, the numerical change corresponding to the data characteristics of the real-time gravity data as the Y-axis, and the gravity direction corresponding to the data characteristics of the real-time rotation vector data as the Z-axis;

[0037] Establish a real-time three-dimensional feature vector for gravity sensing using the data characteristics of the real-time gravitational acceleration data, the data characteristics of the real-time gravity data, and the data characteristics of the real-time rotation vector data;

[0038] Obtain the real-time three-dimensional feature vector corresponding to the t-1 moment and the real-time three-dimensional feature vector corresponding to the t+1 moment of the real-time three-dimensional feature vector for gravity sensing respectively;

[0039] Obtain a numerical change model for gravity sensing using the real-time three-dimensional feature vector at the t-1 moment, the real-time three-dimensional feature vector, and the real-time three-dimensional feature vector at the t+1 moment.

[0040] Furthermore, the gravity sensing data processing results obtained using the gravity sensor data and the gravity sensing three-dimensional unidirectional model include:

[0041] S3-1. Perform numerical continuity calibration processing on the gravity sensor data to obtain the numerical continuity calibration processing result of the gravity sensor data;

[0042] S3-2. Obtain the gravity sensing data processing result according to the gravity sensing three-dimensional unidirectional model using the numerical continuity calibration processing result of the gravity sensor data.

[0043] Furthermore, the numerical continuity calibration processing result obtained by performing numerical continuity calibration processing on the gravity sensor data includes:

[0044] S3-1-1. Determine whether the gravity sensor data corresponding to the standard data processing moment t is different from the gravity sensor data corresponding to the t+1 moment. If so, execute S3-1-2; otherwise, directly execute S3-1-3;

[0045] S3-1-2. Determine whether the gravity sensor data corresponding to the standard data processing moment t is different from the gravity sensor data corresponding to the t-1 moment. If so, the numerical continuity calibration processing results at the t-1 moment, the standard data processing moment t, and the t+1 moment are normal; otherwise, execute S3-1-3;

[0046] S3-1-3. Determine whether the direction of the real-time rotation vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotation vector data corresponding to the time t+1. If it is, re-obtain the direction of the real-time rotation vector data corresponding to the standard data processing time t, and return to S1-2-11. Otherwise, execute S3-1-4;

[0047] S3-1-4. Determine whether the direction of the real-time rotation vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotation vector data corresponding to the time t-1. If it is, re-obtain the direction of the real-time rotation vector data corresponding to the standard data processing time t, and return to S1-2-12. Otherwise, the numerical continuity verification processing result of the values at the time t-1, the standard data processing time t, and the time t+1 is abnormal, and the processing is abandoned;

[0048] Among them, the difference means that the trend of the motion direction corresponding to the gravity sensor of the gravity sensor data corresponding to the standard data processing time t is opposite to the trend of the motion direction corresponding to the gravity sensor data at the time t+1. The same trend of the motion direction means that the trend of the motion direction at the adjacent next moment is within 45 degrees corresponding to the motion direction at the current moment.

[0049] Furthermore, using the numerical continuity verification processing result of the gravity sensor data to obtain the gravity sensing data processing result according to the gravity sensing three-dimensional one-way model includes:

[0050] S3-2-1. Determine whether the numerical continuity verification processing result of the gravity sensor data is normal. If it is, execute S3-2-2. Otherwise, update the standard data processing time t, and return to S1-2-1;

[0051] S3-2-2. Determine whether the real-time motion three-dimensional model corresponding to the gravity sensing three-dimensional one-way model at the standard data processing time t corresponds to the numerical change model. If it is, output the gravity sensing three-dimensional one-way model as the gravity sensing data processing result at the standard data processing time t. Otherwise, execute S3-2-3;

[0052] S3-2-3. Determine whether the direction of the real-time motion three-dimensional model corresponding to the gravity sensing three-dimensional one-way model is the same as the direction of the numerical change model. If it is, output the gravity sensing three-dimensional one-way model as the gravity sensing data processing result at the standard data processing time t. Otherwise, return to S3-1-1;

[0053] Among them, the correspondence between the motion three-dimensional model and the numerical change model means that the inner vectors in the models at the same time correspond.

[0054] Compared with the closest prior art, the beneficial effects of the present invention are:

[0055] By combining the data collected by sensors to construct a three-dimensional coordinate model, not only the numerical magnitude of the gravity data is considered, but also the relevant features behind the data are analyzed. The comprehensive consideration improves the efficiency and accuracy of data processing, and innovatively proposes the concept of a three-dimensional unidirectional model. By virtue of the characteristic of gravity being vertically downward, subsequent feature comparison of the scheme is carried out, realizing the cycle and rapid verification of the logic of the scheme itself. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flowchart of a gravity sensing data processing method for a mobile terminal provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following further details the specific embodiments of the present invention with reference to the accompanying drawings.

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. Embodiment

[0059] The present invention provides a gravity sensing data processing method for a mobile terminal, as Figure 1 shown, including:

[0060] S1. Obtain gravity sensing combined data using the gravity sensor data of the mobile terminal;

[0061] S2. Establish a gravity sensing three-dimensional unidirectional model according to the gravity sensing combined data;

[0062] S3. Obtain a gravity sensing data processing result using the gravity sensor data and the gravity sensing three-dimensional unidirectional model.

[0063] S1 specifically includes:

[0064] S1-1. Respectively obtain real-time gravity acceleration data, real-time gravity data, and real-time rotation vector data based on the gravity sensor data;

[0065] S1-2. Respectively obtain the data characteristics of the real-time gravity acceleration data, the data characteristics of the real-time gravity data, and the data characteristics of the real-time rotation vector data according to the real-time gravity acceleration data, the real-time gravity data, and the real-time rotation vector data;

[0066] S1-3. Use the real-time gravitational acceleration data, real-time gravity data, real-time rotation vector data, data features of the real-time gravitational acceleration data, data features of the real-time gravity data, and data features of the real-time rotation vector data as gravity sensing combined data.

[0067] In this embodiment, a method for processing gravity sensing data for a mobile terminal. The gravitational acceleration data, gravity data, and rotation vector data are collected and transmitted jointly by the following sensors, including: an action sensor, an acceleration sensor, a gyroscope sensor, a gravity sensor, a linear acceleration sensor, and a rotation vector sensor.

[0068] S1-2 specifically includes:

[0069] S1-2-1. Use the corresponding moment of the real-time gravitational acceleration data as the standard data processing moment t;

[0070] S1-2-2. Obtain the gravitational acceleration data at the t - 1 moment and the gravitational acceleration data at the t + 1 moment respectively;

[0071] S1-2-3. Obtain the change rate of the gravitational acceleration data as the first change rate according to the gravitational acceleration data at the t - 1 moment and the real-time gravitational acceleration data at the standard data processing moment t;

[0072] S1-2-4. Obtain the change rate of the gravitational acceleration data as the second change rate according to the real-time gravitational acceleration data at the standard data processing moment t and the gravitational acceleration data at the t + 1 moment;

[0073] S1-2-5. Use the first change rate and the second change rate as the data features of the real-time gravitational acceleration data;

[0074] S1-2-6. Obtain the real-time gravity data at the t - 1 moment and the real-time gravity data at the t + 1 moment respectively;

[0075] S1-2-7. Use the real-time gravity data at the t - 1 moment and the real-time gravity data at the standard data processing moment t to obtain the change trend of the gravity data as the first trend;

[0076] S1-2-8. Use the real-time gravity data at the standard data processing moment t and the real-time gravity data at the t + 1 moment to obtain the change trend of the gravity data as the second trend;

[0077] S1-2-9. Use the first trend and the second trend as the data features of the real-time gravity data;

[0078] S1-2-10. Obtain the real-time rotation vector data at the t - 1 moment and the real-time rotation vector data at the t + 1 moment respectively;

[0079] S1-2-11. Obtain the relative change angle of the rotation vector data using the real-time rotation vector data at time t-1 and the real-time rotation vector data at the standard data processing time t as the first relative change angle;

[0080] S1-2-12. Obtain the relative change angle of the rotation vector data using the real-time rotation vector data at the standard data processing time t and the real-time rotation vector data at time t+1 as the second relative change angle;

[0081] S1-2-13. Use the first relative change angle and the second relative change angle as the data characteristics of the real-time rotation vector data.

[0082] S2-1 specifically includes:

[0083] S2-1-1. Establish a real-time three-dimensional motion model of gravity induction using the real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data of the gravity induction combined data;

[0084] S2-1-2. Establish a numerical change model of gravity induction using the data characteristics of the real-time gravitational acceleration data, the data characteristics of the real-time gravity data, and the data characteristics of the real-time rotation vector data;

[0085] S2-1-3. Use the real-time three-dimensional motion model of gravity induction and the numerical change model as the three-dimensional one-way model of gravity induction.

[0086] S2-1-1 specifically includes:

[0087] S2-1-1-1. Establish a basic motion three-dimensional coordinate system using the corresponding time sequence of the real-time gravitational acceleration data of the gravity induction combined data as the X-axis, the numerical change of the real-time gravity data of the gravity induction combined data as the Y-axis, and the corresponding motion direction of the real-time rotation vector data of the gravity induction combined data as the Z-axis;

[0088] S2-1-1-2. Establish a real-time three-dimensional vector of the gravity induction combined data according to the basic motion three-dimensional coordinate system using the real-time gravitational acceleration data, real-time gravity data, and real-time rotation vector data of the gravity induction combined data;

[0089] S2-1-1-3. Obtain the real-time three-dimensional vector corresponding to time t-1 and the real-time three-dimensional vector corresponding to time t+1 of the real-time three-dimensional vector of the gravity induction combined data respectively;

[0090] S2-1-1-4. Obtain the real-time three-dimensional motion model of gravity induction using the real-time three-dimensional vector at time t-1, the real-time three-dimensional vector, and the real-time three-dimensional vector at time t+1.

[0091] S2-1-2 specifically includes:

[0092] S2-1-2-1. Establish a fixed Z-axis three-dimensional coordinate system for basic gravity sensing with the time series corresponding to the data characteristics of the real-time gravitational acceleration data as the X-axis, the numerical change corresponding to the data characteristics of the real-time gravity data as the Y-axis, and the gravity direction corresponding to the data characteristics of the real-time rotation vector data as the Z-axis;

[0093] S2-1-2-2. Establish a real-time three-dimensional feature vector for gravity sensing using the data characteristics of the real-time gravitational acceleration data, the data characteristics of the real-time gravity data, and the data characteristics of the real-time rotation vector data;

[0094] S2-1-2-3. Obtain the real-time three-dimensional feature vector corresponding to the t-1 moment and the real-time three-dimensional feature vector corresponding to the t+1 moment of the real-time three-dimensional feature vector for gravity sensing respectively;

[0095] S2-1-2-4. Obtain a numerical change model for gravity sensing using the real-time three-dimensional feature vector at the t-1 moment, the real-time three-dimensional feature vector, and the real-time three-dimensional feature vector at the t+1 moment.

[0096] S3 specifically includes:

[0097] S3-1. Perform numerical continuity calibration processing on the gravity sensor data to obtain the result of numerical continuity calibration processing of the gravity sensor data;

[0098] S3-2. Obtain the gravity sensing data processing result according to the gravity sensing three-dimensional unidirectional model using the result of numerical continuity calibration processing of the gravity sensor data.

[0099] S3-1 specifically includes:

[0100] S3-1-1. Determine whether the gravity sensor data corresponding to the standard data processing moment t is different from the gravity sensor data corresponding to the t+1 moment. If so, execute S3-1-2; otherwise, directly execute S3-1-3;

[0101] S3-1-2. Determine whether the gravity sensor data corresponding to the standard data processing moment t is different from the gravity sensor data corresponding to the t-1 moment. If so, the numerical continuity calibration processing results at the t-1 moment, the standard data processing moment t, and the t+1 moment are normal; otherwise, execute S3-1-3;

[0102] S3-1-3. Determine whether the direction of the real-time rotation vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotation vector data corresponding to the time t+1. If it is, re-obtain the direction of the real-time rotation vector data corresponding to the standard data processing time t, and return to S1-2-11. Otherwise, execute S3-1-4;

[0103] S3-1-4. Determine whether the direction of the real-time rotation vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotation vector data corresponding to the time t-1. If it is, re-obtain the direction of the real-time rotation vector data corresponding to the standard data processing time t, and return to S1-2-12. Otherwise, the numerical continuity verification processing result of the values at the time t-1, the standard data processing time t, and the time t+1 is abnormal, and the processing is abandoned;

[0104] Among them, the difference means that the motion direction trends of the gravity sensor data corresponding to the standard data processing time t and the gravity sensor data corresponding to the time t+1 are opposite, and the same motion direction trend means that the motion direction trend of the adjacent next moment is within 45 degrees of the motion direction corresponding to the current moment.

[0105] S3-2 specifically includes:

[0106] S3-2-1. Determine whether the numerical continuity verification processing result of the gravity sensor data is normal. If it is, execute S3-2-2. Otherwise, update the standard data processing time t, and return to S1-2-1;

[0107] S3-2-2. Determine whether the real-time motion three-dimensional model corresponding to the gravity induction three-dimensional one-way model at the standard data processing time t corresponds to the numerical change model. If it is, output the gravity induction three-dimensional one-way model as the gravity induction data processing result at the standard data processing time t. Otherwise, execute S3-2-3;

[0108] S3-2-3. Determine whether the direction of the real-time motion three-dimensional model corresponding to the gravity induction three-dimensional one-way model is the same as the direction of the numerical change model. If it is, output the gravity induction three-dimensional one-way model as the gravity induction data processing result at the standard data processing time t. Otherwise, return to S3-1-1;

[0109] Among them, the correspondence between the motion three-dimensional model and the numerical change model means that the inner vectors in the models at the same time correspond.

[0110] In this embodiment, a method for processing gravity induction data for a mobile terminal, the directions of the real-time motion three-dimensional model and the numerical change model involve the actual device motion direction. However, in the actual deployment of the solution, the actual definition of the direction can be adjusted to the included angle between the motion direction and the gravity direction according to the accuracy requirements.

[0111] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0112] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0113] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: still modifications or equivalent replacements can be made to the specific implementation manners of the present invention, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A gravity sensing data processing method for a mobile terminal, characterized in that: include: S1. Obtaining gravity sensing combined data using the gravity sensor data of the mobile terminal; S1-1, respectively acquiring real-time gravity acceleration data, real-time gravity data and real-time rotation vector data based on the gravity sensor data; S1-2, respectively obtaining data features of the real-time gravity acceleration data, data features of the real-time gravity data, and data features of the real-time rotation vector data according to the real-time gravity acceleration data, the real-time gravity data, and the real-time rotation vector data; S1-3, using the real-time gravity acceleration data, the real-time gravity data, the real-time rotation vector data, the data features of the real-time gravity acceleration data, the data features of the real-time gravity data and the data features of the real-time rotation vector data as gravity sensing combined data; S2. establishing a gravity sensing three-dimensional unidirectional model according to the gravity sensing combined data; S2-1, using the real-time gravity acceleration data, real-time gravity data and real-time rotation vector data of the gravity sensing combined data to establish a real-time motion three-dimensional model of gravity sensing; S2-1-1, using the corresponding time series of the real-time gravity acceleration data of the gravity sensing combined data as the X-axis, the real-time gravity data value change of the gravity sensing combined data as the Y-axis and the corresponding movement direction of the real-time rotation vector data of the gravity sensing combined data as the Z-axis to establish a basic motion three-dimensional coordinate system; S2-1-2, using the real-time gravity acceleration data, real-time gravity data and real-time rotation vector data of the gravity sensing combined data to establish a real-time three-dimensional vector of the gravity sensing combined data according to the basic motion three-dimensional coordinate system; S2-1-3, respectively obtaining the real-time three-dimensional vector of the gravity sensing combined data corresponding to the real-time three-dimensional vector at time t-1 and the real-time three-dimensional vector at time t+1; S2-1-4, using the real-time three-dimensional vector at time t-1, the real-time three-dimensional vector at time t and the real-time three-dimensional vector at time t+1 to obtain a real-time motion three-dimensional model of gravity sensing; S2-2, establishing a numerical change model of gravity sensing by using the data features of the real-time gravity acceleration data, the data features of the real-time gravity data and the data features of the real-time rotation vector data; S2-3, using the real-time motion three-dimensional model of gravity sensing and the numerical change model as a three-dimensional one-way model of gravity sensing; S3. Obtaining a gravity sensing data processing result using the gravity sensor data and the gravity sensing three-dimensional unidirectional model.

2. A gravity sensing data processing method for a mobile terminal as claimed in claim 1, characterized in that: According to the real-time gravity acceleration data, the real-time gravity data and the real-time rotation vector data, respectively obtaining data features of the real-time gravity acceleration data, data features of the real-time gravity data and data features of the real-time rotation vector data includes: S1-2-1, using the corresponding time of the real-time gravity acceleration data as the standard data processing time t; S1-2-2, respectively obtain the gravity acceleration data at time t-1 and the gravity acceleration data at time t+1; S1-2-3, obtaining a change rate of gravity acceleration data as a first change rate based on the gravity acceleration data at time t-1 and the real-time gravity acceleration data at the standard data processing time t; S1-2-4, obtaining the change rate of gravity acceleration data as the second change rate based on the real-time gravity acceleration data at time t and the gravity acceleration data at time t+1 according to the standard data processing; S1-2-5, using the first change rate and the second change rate as data features of real-time gravity acceleration data; S1-2-6, respectively obtaining the real-time gravity data at time t-1 and the real-time gravity data at time t+1; S1-2-7, using the real-time gravity data at time t-1 and the standard data to process the real-time gravity data at time t to obtain a change trend of the gravity data as a first trend; S1-2-8. Using the standard data to process the real-time gravity data at time t and the real-time gravity data at time t+1, obtain a change trend of the gravity data as a second trend; S1-2-9, using the first trend and the second trend as data features of real-time gravity data; S1-2-10, respectively obtaining the real-time rotating vector data at time t-1 and the real-time rotating vector data at time t+1; S1-2-11, using the real-time rotating vector data at time t-1 and the real-time rotating vector data at time t of standard data processing to obtain the relative change angle of the rotating vector data as the first relative change angle; S1-2-12, using the standard data to process the real-time rotation vector data at time t and the real-time rotation vector data at time t+1 to obtain the relative change angle of the rotation vector data as the second relative change angle; S1-2-13. Use the first relative change angle and the second relative change angle as data features of real-time rotation vector data.

3. A gravity sensing data processing method for a mobile terminal as claimed in claim 1, characterized in that: Establishing a numerical change model of gravity sensing by using the data features of the real-time gravity acceleration data, the data features of the real-time gravity data and the data features of the real-time rotation vector data includes: A fixed Z-axis three-dimensional coordinate system of basic gravity sensing is established by using the data feature corresponding to the time series of the real-time gravity acceleration data as the X-axis, the data feature corresponding to the value change of the real-time gravity data as the Y-axis, and the data feature corresponding to the gravity direction of the real-time rotation vector data as the Z-axis; Establishing a real-time three-dimensional feature vector of gravity sensing by using the data features of the real-time gravity acceleration data, the data features of the real-time gravity data and the data features of the real-time rotation vector data; Respectively obtain the real-time three-dimensional feature vector of the gravity sensing corresponding to the real-time three-dimensional feature vector at time t-1 and the real-time three-dimensional feature vector at time t+1; The numerical change model of gravity sensing is obtained by using the real-time three-dimensional feature vector at time t-1, the real-time three-dimensional feature vector at time t, and the real-time three-dimensional feature vector at time t+1.

4. A gravity sensing data processing method for a mobile terminal as claimed in claim 1, characterized in that: The gravity sensing data processing result obtained by using the gravity sensor data and the gravity sensing three-dimensional unidirectional model includes: S3-1, performing a numerical continuity calibration process on the gravity sensor data to obtain a numerical continuity calibration process result of the gravity sensor data; S3-2. Obtain a gravity sensing data processing result according to a gravity sensing three-dimensional unidirectional model by using the numerical continuity calibration processing result of the gravity sensor data.

5. A gravity sensing data processing method for a mobile terminal as claimed in claim 4, characterized in that: The numerical continuity calibration processing of the gravity sensor data is performed using the gravity sensor data to obtain the numerical continuity calibration processing result of the gravity sensor data, including: S3-1-1, determine whether the gravity sensor data corresponding to the standard data processing time t is different from the gravity sensor data corresponding to the time t+1, if so, execute S3-1-2, otherwise, directly execute S3-1-3; S3-1-2, determine whether the gravity sensor data corresponding to the standard data processing time t is different from the gravity sensor data corresponding to the time t-1. If so, the value continuity calibration processing result of the time t-1, the standard data processing time t and the time t+1 is normal. Otherwise, execute S3-1-3; S3-1-3, determine whether the direction of the real-time rotating vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotating vector data corresponding to the time t+1. If so, re-obtain the direction of the real-time rotating vector data corresponding to the standard data processing time t and return to S1-2-11. Otherwise, execute S3-1-4; S3-1-4, determine whether the direction of the real-time rotating vector data corresponding to the standard data processing time t is the same as the direction of the real-time rotating vector data corresponding to the time t-1. If so, re-acquire the direction of the real-time rotating vector data corresponding to the standard data processing time t, and return to S1-2-12. Otherwise, the result of the numerical continuity calibration processing at the time t-1, the standard data processing time t and the time t+1 is abnormal, and the processing is abandoned; Among them, the difference is that the gravity sensor data corresponding to the standard data processing time t and the gravity sensor data corresponding to the gravity sensor data at time t+1 have opposite movement direction trends, and the same movement direction trend is that the movement direction trend at the next adjacent moment is within 45 degrees of the movement direction at the current moment.

6. A gravity sensing data processing method for a mobile terminal as claimed in claim 5, characterized in that: The gravity sensing data processing result obtained by using the numerical continuity calibration processing result of the gravity sensor data according to the gravity sensing three-dimensional unidirectional model includes: S3-2-1, determine whether the result of the numerical continuity calibration of the gravity sensor data is normal, if so, proceed to S3-2-2, otherwise, update the standard data processing time t, and return to S1-2-1; S3-2-2, determine whether the real-time motion three-dimensional model and the numerical change model corresponding to the gravity sensing three-dimensional unidirectional model at the standard data processing time t correspond to each other, if so, output the gravity sensing three-dimensional unidirectional model as the gravity sensing data processing result at the standard data processing time t, otherwise, execute S3-2-3; S3-2-3, determine whether the direction of the gravity sensing three-dimensional unidirectional model corresponding to the real-time motion three-dimensional model is the same as the direction of the numerical change model, if so, output the gravity sensing three-dimensional unidirectional model as the gravity sensing data processing result at the standard data processing time t, otherwise, return to S3-1-1; The motion three-dimensional model and the numerical change model correspond to each other as the internal vectors of the models at the same time.

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