CN105403219A - Bicycle navigation system based on MEMS (Micro-electromechanical Systems) - Google Patents

Abstract

The invention provides a bicycle navigation system based on MEMS (Micro-electromechanical Systems). The bicycle navigation system comprises a route measurement module, a vehicle speed detection module, a collision detection module, a rollover detection module, a posture detection module and/or a navigation module. By virtue of the bicycle navigation system, a navigation problem of a bicycle can be solved, a current position of a user is displayed in real time and dynamic posture information of the bicycle is output in real time; the speed and route of the bicycle can be detected, the user is reminded of preventing the bicycle of rollover, and the collision detection module can provide accident evaluation and rescue-calling services.

Description

A kind of bicycle navigational system based on MEMS

Technical field

The present invention relates to navigation and localization field, particularly relates to a kind of bicycle navigational system based on MEMS.

Background technology

Modern society advocates low-carbon (LC) and energy conservation culture, bicycle is a kind of vehicles of low-carbon environment-friendly, deeply favored by users, but, when use cycling enter the alameda in field, mountain valley and tunnel time, gps satellite signal covers by barrier, cannot use traditional satellite navigation.In addition, a lot of navigating instrument is not suitable with bicycle navigation at present, and such as, present code table cannot provide the attitude information in bicycle running process.

Therefore, be necessary to propose a kind of new scheme.

Summary of the invention

The object of the invention is to the defect overcoming prior art, a kind of bicycle navigational system based on MEMS is provided, it can solve the navigation problem of bicycle, the current location of real-time display user, the real-time dynamic attitude information output from driving, speed and the stroke of bicycle can also be detected, reminding user prevents bicycle from turning on one's side, and collision detection module can provide accident to identify and calling rescue service.

For reaching aforementioned object, the bicycle navigational system based on MEMS of the present invention, this bicycle navigational system comprises: stroke measurment module, Bus-Speed Monitoring module, collision detection module, rollover detection module, attitude detection module and/or navigation module.

As the present invention one preferred embodiment, described stroke measurment module comprises by AMR geomagnetic sensor and magnet, some A (0,0) be the central shaft of wheel, some B (x, y) is the point on wheel external diameter, AB is the radius r of wheel, then the girth C of wheel is:

C＝2πr；

E (e ₁, e ₂) point be bicycle spoke on a bit, this E point is installed magnet;

D (d ₁, d ₂) point is the point of fixity of bicycle rear upper branch, and this D point is installed geomagnetic sensor;

In cycling process, the magnet signal intensity sensed by detecting geomagnetic sensor records vehicle wheel rotation number of turns n, thus can calculate the stroke S of bicycle:

S＝C×n＝2πr×n。

As the present invention one preferred embodiment, described Bus-Speed Monitoring module, is tested the speed by AMR geomagnetic sensor:

The magnet signal of two same characteristic features is detected by AMR geomagnetic sensor, and the sampling number N between these two magnet signal intensities cumulative, adopt the bicycle girth C calculated, then the speed of a motor vehicle computing formula of bicycle is as follows:

$V=\frac{C}{N\×T}$

In formula, T is the sampling period.

As the present invention one preferred embodiment, the attitude that described attitude detection module energy prompting bicycle is current, if initial time exists GPS supplementary module, the traveling orientation of bicycle can be determined in real time:

When bicycle is in accurate stationary state, described accurate stationary state comprises static and at the uniform velocity state, and obtain bicycle initial state information by the output valve resolving accelerometer, described bicycle initial state information comprises pitching and roll information;

When bicycle is kept in motion, relies on gyro output valve to carry out bicycle posture renewal, and accelerometer can be used to assist gyroscopic drift compensation and attitude correction.

As the present invention one preferred embodiment, the dynamic Attitude Algorithm flow process of bicycle is specially:

Before cycling, the drift of gyro is corrected, gathers bicycle gyro output valve under static state and accumulated samples is counted, the output valve of gyro is averaging:

$\mathrm{\ϵ}=\frac{\underset{i=1}{\overset{N}{\Σ}}{\mathrm{\ω}}_i}{N}$

In formula, ε is gyroscopic drift, ω _ifor gyro output valve, N is sampling number;

Before cycling, use acceleration of gravity to calculate the attitude angle of bicycle in the projection components of three axis accelerometer, described attitude angle comprises the angle of pitch and roll angle:

$\left\{\begin{array}{c}\mathrm{\θ}=asin\frac{a_y}{\sqrt{a_x^2+a_y^2+a_z^2}}\\ \mathrm{\γ}=asin\frac{a_x}{\sqrt{a_x^2+a_y^2+a_z^2}}\end{array}\right.$

In formula, θ is the angle of pitch, and γ is roll angle, a _x, a _yand a _zbe respectively the projection components of acceleration of gravity in three axis accelerometer;

Adopt hypercomplex number Attitude Algorithm to upgrade the attitude information of bicycle, wherein, the transformational relation of hypercomplex number and Eulerian angle is:

$\left\{\begin{array}{c}\mathrm{\θ}=atan\left(\frac{Q_0{Q}_1+Q_2{Q}_3}{1-2(Q_1^2+Q_2^2)}\right)\\ \mathrm{\γ}=a\sin (Q_0{Q}_2-Q_3{Q}_1)\end{array}\right.$

In formula, Q is attitude quaternion, and θ is the angle of pitch, and γ is roll angle;

Accelerometer assists gyroscopic drift compensation and attitude correction algorithm flow:

Calculate the acceleration value a of each sampling instant bicycle, and to be stored in length be in N buffer zone:

$a=\sqrt{a_x^2+a_y^2+a_z^2}$

In formula, a _x, a _yand a _zbe respectively three axle components of accelerometer;

If the vector value a of current time acceleration meets | a-g| < λ, then centered by this puts, N number of acceleration value before and after storing, setting up a length is the data buffer of 2N+1, and calculates the standard deviation sigma (a) of acceleration value in data buffer;

If then think that bicycle is in accurate stationary state:

$\left\{\begin{array}{c}\mathrm{\&sigma;}\left(a\right)=\sqrt{\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{\left(a_i-\stackrel{\&OverBar;}{a}\right)}^2}{2N+1}}\\ \stackrel{\&OverBar;}{a}=\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{a}_i}{2N+1}\end{array}\right.$

In formula, a _ifor the acceleration value in buffer zone;

If bicycle is in accurate stationary state, utilize the output valve of accelerometer to recalculate attitude, and reset the attitude information in the dynamic Attitude Algorithm of bicycle.

As the present invention one preferred embodiment, when bicycle crashes, described collision detection module can preserve bicycle collision information, and described collision information comprises current speed and acceleration, and uploads to cloud server by mobile phone application.

As the present invention one preferred embodiment, bicycle collision detection modular algorithm flow process:

If the accekeration of bicycle forward direction is a, setting up length is that the buffer zone W store sample of m obtains forward acceleration;

After the data in the W of buffer zone obtain upgrading, detect it one by one and store data and whether be negative and the absolute value data number n that whether is greater than threshold epsilon and meets this condition continuously;

If n > is m/2, then think that bicycle and barrier there occurs collision;

Calculate the kinetic energy of bicycle when colliding to be expressed as follows:

$W=\frac{1}{2}{\mathrm{mV}}^2$

In formula, W is the kinetic energy of bicycle, and m is the quality of people and bicycle, speed when V is collision.

As the present invention one preferred embodiment, bicycle side looks through and surveys modular algorithm flow process:

If the roll angle that dynamically gesture module exports is γ, setting up length is that the buffer zone W of m is to store the roll angle of current time;

After the data in the W of buffer zone obtain renewal, detect the number n whether its absolute value storing data is greater than threshold epsilon and meets this condition continuously one by one;

If n > is m/2, then think that bicycle there occurs rollover.

As the present invention one preferred embodiment, stroke measurment module and Bus-Speed Monitoring module measure the current stroke of bicycle and velocity information respectively, the moment of cycling is started user, the alternate position spike score value using GPS former and later two moment of receiving end to export calculates the initial orientation of bicycle, gyro output valve constantly updates bicycle orientation, and the method for utilization dead reckoning can in real time output from the current position coordinates of driving.

As the present invention one preferred embodiment, GPS information determination bicycle orientation algorithm flow:

Suppose that the initial orientation of bicycle is ψ ₀, utilize the output valve of gyro to upgrade attitude and the azimuth information of bicycle;

When bicycle is kept in motion, and when GPS chip receives signals clear is covered, the latitude and longitude information utilizing GPS chip to export, fix the position ψ;

$\mathrm{\&psi;}=atan\frac{\mathrm{\&Delta;}\mathrm{\&lambda;}}{\mathrm{\&Delta;}L}$

The orientation ψ utilizing GPS information measurement to obtain resets the orientation values in dynamic Attitude Algorithm, and upgrades attitude information:

In formula, θ is the angle of pitch, for roll angle, ψ is position angle, and Q is attitude quaternion;

Bicycle navigation algorithm flow:

By bicycle displacement according to current orientation travel direction cosine decomposition, project to east orientation and north orientation respectively, the traveling-position of bicycle can be determined:

$\left\{\begin{array}{c}{x}_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{sin\&psi;}}_i\\ y_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;y}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{cos\&psi;}}_i\end{array}\right.$

In formula, S represents the girth of bicycle, ψ _irepresent the orientation of bicycle, x _nrepresent east orientation displacement, y _nrepresent north orientation displacement;

The bicycle position coordinates obtained is converted to latitude and longitude information, imports mobile phone A PP map software by bluetooth module, the current location of user can be shown in real time.

Beneficial effect of the present invention: compared with prior art, tool of the present invention has the following advantages:

(1) the bicycle navigational system based on MEMS of the present invention, solves the navigation problem of the bicycle when not having gps signal based on MEMS inertial technology.

(2) the bicycle navigational system based on MEMS of the present invention, imports mobile phone A PP map software by navigation data by bluetooth, can show the current location of user in real time.

(3) the bicycle navigational system based on MEMS of the present invention, in real time output from the dynamic attitude information of driving.

(4) the bicycle navigational system based on MEMS of the present invention, utilizes AMR geomagnetic sensor to detect the speed of bicycle.

(5) the bicycle navigational system based on MEMS of the present invention, utilizes AMR geomagnetic sensor to detect the stroke of bicycle.

(6) can prevent bicycle from turning on one's side by reminding user under complex road condition.

(7) collision checking function can provide accident to identify and calling rescue service.

Accompanying drawing explanation

Fig. 1 is the system chart of the bicycle navigational system that the present invention is based on MEMS;

Fig. 2 is the schematic diagram that bicycle displacement calculates;

Fig. 3 is that bicycle collision and rollover detect schematic diagram;

Fig. 4 is the dynamic attitude updating algorithm process flow diagram of bicycle;

Fig. 5 is bicycle dead reckoning schematic diagram.

Embodiment

Below in conjunction with accompanying drawing, the present invention is described in further detail.

Alleged herein " embodiment " or " embodiment " refers to special characteristic, structure or the characteristic that can be contained at least one implementation of the present invention.Different local in this manual " in one embodiment " occurred not all refers to same embodiment, neither be independent or optionally mutually exclusive with other embodiments embodiment.

Refer to Fig. 1.Fig. 1 is the system chart of the bicycle navigational system that the present invention is based on MEMS.As shown in Figure 1, bicycle navigational system comprises: stroke measurment module, Bus-Speed Monitoring module, collision detection module, rollover detection module, attitude detection module and navigation module.

Described stroke measurment module is primarily of AMR geomagnetic sensor and magnet composition.Fig. 2 is the schematic diagram of bicycle climb displacement, and great circle represents bicycle rear wheel, and some A (0,0) is the central shaft of wheel, and some B (x, y) is the point on wheel external diameter, and AB is the radius r of wheel, then the girth C of wheel is:

C＝2πr

E (e ₁, e ₂) point be bicycle spoke on a bit, this E point installs magnet.D (d ₁, d ₂) point is the point of fixity of bicycle rear upper branch, installs geomagnetic sensor at that point.In cycling process, the magnet signal intensity sensed by detecting geomagnetic sensor records vehicle wheel rotation number of turns n, thus can calculate the stroke S of bicycle:

S＝C×n＝2πr×n

Described Bus-Speed Monitoring module, is tested the speed by AMR geomagnetic sensor, and its principle of work is the magnetic signal that AMR geomagnetic sensor detects two same characteristic features, and the sampling number N between these two magnetic signal intensity cumulative.Adopt the above-mentioned bicycle girth C calculated, then the speed of a motor vehicle computing formula of bicycle is as follows:

$V=\frac{C}{N\&times;T}$

In formula, T is the sampling period.

Described attitude detection module can the current attitude of prompting bicycle, assists, can determine the traveling orientation of bicycle in real time if initial time exists GPS information.Its principle of work is when bicycle is in accurate stationary state (static and at the uniform velocity), can be obtained the initial state information (pitching and roll) of bicycle by the output valve resolving accelerometer.When bicycle is kept in motion, gyro output valve can be relied on to carry out bicycle posture renewal, and accelerometer can be used to assist gyroscopic drift compensation and attitude correction, its algorithm flow as shown in Figure 4.

The dynamic Attitude Algorithm flow process of bicycle:

Before cycling, the drift of gyro is corrected.Gather bicycle gyro output valve under static state and accumulated samples is counted, the output valve of gyro is averaging.

$\mathrm{\&epsiv;}=\frac{\underset{i=1}{\overset{N}{\&Sigma;}}{\mathrm{\&omega;}}_i}{N}$

In formula, ε is gyroscopic drift, ω _ifor gyro output valve, N is sampling number.

Before cycling, acceleration of gravity is used to calculate the attitude angle (angle of pitch and roll angle) of bicycle in the projection components of three axis accelerometer.

$\left\{\begin{array}{c}\mathrm{\&theta;}=asin\frac{a_y}{\sqrt{a_x^2+a_y^2+a_z^2}}\\ \mathrm{\&gamma;}=asin\frac{a_x}{\sqrt{a_x^2+a_y^2+a_z^2}}\end{array}\right.$

In formula, θ is the angle of pitch, and γ is roll angle, a _x, a _yand a _zbe respectively the projection components of acceleration of gravity in three axis accelerometer.

Adopt hypercomplex number Attitude Algorithm to upgrade the attitude information of bicycle, algorithm flow as shown in Figure 4.Wherein, the transformational relation of hypercomplex number and Eulerian angle is:

$\left\{\begin{array}{c}\mathrm{\&theta;}=atan\left(\frac{Q_0{Q}_1+Q_2{Q}_3}{1-2(Q_1^2+Q_2^2)}\right)\\ \mathrm{\&gamma;}=a\sin (Q_0{Q}_2-Q_3{Q}_1)\end{array}\right.$

In formula, Q is attitude quaternion, and θ is the angle of pitch, and γ is roll angle.

Accelerometer assists gyroscopic drift compensation and attitude correction algorithm flow:

Calculate the acceleration value a of each sampling instant bicycle, and to be stored in length be in N buffer zone.

$a=\sqrt{a_x^2+a_y^2+a_z^2}$

In formula, a _x, a _yand a _zbe respectively three axle components of accelerometer.

If the vector value a of current time acceleration meets | a-g| < λ, then centered by this puts, N number of acceleration value before and after storing, setting up a length is the data buffer of 2N+1, and calculates the standard deviation sigma (a) of acceleration value in data buffer.If then think that bicycle is in accurate stationary state.

$\left\{\begin{array}{c}\mathrm{\&sigma;}\left(a\right)=\sqrt{\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{\left(a_i-\stackrel{\&OverBar;}{a}\right)}^2}{2N+1}}\\ \stackrel{\&OverBar;}{a}=\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{a}_i}{2N+1}\end{array}\right.$

In formula, a _ifor the acceleration value in buffer zone.

If bicycle is in accurate stationary state, utilize the output valve of accelerometer to recalculate attitude, and reset the attitude information in the dynamic Attitude Algorithm of bicycle.Utilize the output valve of gyro to calculate gyroscopic drift, gyroscopic drift computing method are with reference to the dynamic Attitude Algorithm flow process of bicycle.

Described collision detection module, as shown in Figure 3, when bicycle crashes, bicycle collision information (current speed and acceleration) can be preserved and upload to cloud server by mobile phone A PP and identify for accident responsibility, call out rescue service simultaneously.Its principle of work is when bicycle body collides time, and larger change will occur the forward acceleration value of bicycle.

Bicycle collision detection modular algorithm flow process is as follows:

If the accekeration of bicycle forward direction is a, setting up length is that the buffer zone W store sample of m obtains forward acceleration.

After the data in the W of buffer zone obtain upgrading, detect it one by one and store data and whether be negative and the absolute value data number n that whether is greater than threshold epsilon and meets this condition continuously.

If n > is m/2, then think that bicycle and barrier there occurs collision.

Calculate the kinetic energy of bicycle when colliding to be expressed as follows:

$W=\frac{1}{2}{\mathrm{mV}}^2$

In formula, W is the kinetic energy of bicycle, and m is the quality of people and bicycle, speed when V is collision.

Described rollover detection module, as shown in Figure 3, can prevent bicycle from turning on one's side at reminding user under complex road condition, and its principle is that larger change will occur the roll angle of bicycle when rollover occurs in bicycle body time.

It is as follows that bicycle side looks through survey modular algorithm flow process:

If the roll angle that dynamically gesture module exports is γ, setting up length is that the buffer zone W of m is to store the roll angle of current time.

After the data in the W of buffer zone obtain renewal, detect the number n whether its absolute value storing data is greater than threshold epsilon and meets this condition continuously one by one.

If n > is m/2, then think that bicycle there occurs rollover.

Described navigation module can solve the navigation problem in the section that gps satellite signal covers by barrier.Its principle is: the stroke that described stroke measurment module and Bus-Speed Monitoring module provide bicycle current respectively and velocity information, the moment of cycling is started user, the alternate position spike score value using GPS former and later two moment of receiving end to export can calculate the initial orientation of bicycle, and gyro output valve constantly update bicycle orientation, then use dead reckoning method can in real time output from drive a vehicle current position coordinates.

GPS information determination bicycle orientation algorithm flow:

Suppose that the initial orientation of bicycle is ψ 0, utilize the output valve of gyro to upgrade attitude and the azimuth information of bicycle, concrete with reference to the dynamic Attitude Algorithm of bicycle.

When bicycle is kept in motion, and when GPS chip receives signals clear is covered, the latitude and longitude information utilizing GPS chip to export, fix the position ψ.

$\mathrm{\&psi;}=atan\frac{\mathrm{\&Delta;}\mathrm{\&lambda;}}{\mathrm{\&Delta;}L}$

The orientation ψ utilizing GPS information measurement to obtain resets the orientation values in dynamic Attitude Algorithm, and upgrades attitude information.

In formula, θ is the angle of pitch, for roll angle, ψ is position angle, and Q is attitude quaternion.

Bicycle navigation algorithm flow is as follows:

As shown in Figure 5, by bicycle displacement according to current orientation travel direction cosine decomposition, project to east orientation and north orientation respectively, the traveling-position of bicycle can be determined.

$\left\{\begin{array}{c}{x}_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{sin\&psi;}}_i\\ y_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;y}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{cos\&psi;}}_i\end{array}\right.$

In formula, S represents the girth of bicycle, ψ _irepresent the orientation of bicycle, x _nrepresent east orientation displacement, y _nrepresent north orientation displacement.

The bicycle position coordinates obtained is converted to latitude and longitude information, imports mobile phone A PP map software by bluetooth module, the current location of user can be shown in real time.

In another embodiment, bicycle navigational system comprises stroke measurment module, Bus-Speed Monitoring module, collision detection module, rollover detection module, attitude detection module or navigation module.

Tool of the present invention has the following advantages:

(1) the bicycle navigational system based on MEMS of the present invention, solves the navigation problem of the bicycle when not having gps signal based on MEMS inertial technology.

(2) the bicycle navigational system based on MEMS of the present invention, imports mobile phone A PP map software by navigation data by bluetooth, can show the current location of user in real time.

(3) the bicycle navigational system based on MEMS of the present invention, in real time output from the dynamic attitude information of driving.

(4) the bicycle navigational system based on MEMS of the present invention, utilizes AMR geomagnetic sensor to detect the speed of bicycle.

(5) the bicycle navigational system based on MEMS of the present invention, utilizes AMR geomagnetic sensor to detect the stroke of bicycle.

(6) can prevent bicycle from turning on one's side by reminding user under complex road condition.

(7) collision checking function can provide accident to identify and calling rescue service.

Above-mentioned explanation fully discloses the specific embodiment of the present invention.It is pointed out that the scope be familiar with person skilled in art and any change that the specific embodiment of the present invention is done all do not departed to claims of the present invention.Correspondingly, the scope of claim of the present invention is also not limited only to previous embodiment.

Claims (10)

1. based on a bicycle navigational system of MEMS, it is characterized in that: this bicycle navigational system comprises: stroke measurment module, Bus-Speed Monitoring module, collision detection module, rollover detection module, attitude detection module and/or navigation module.

2. bicycle navigational system according to claim 1, it is characterized in that: described stroke measurment module comprises by AMR geomagnetic sensor and magnet, point A (0,0) be the central shaft of wheel, point B (x, y) be point on wheel external diameter, AB is the radius r of wheel, then the girth C of wheel is:

C＝2πr；

E (e ₁, e ₂) point be bicycle spoke on a bit, this E point is installed magnet;

D (d ₁, d ₂) point is the point of fixity of bicycle rear upper branch, and this D point is installed geomagnetic sensor;

In cycling process, the magnet signal intensity sensed by detecting geomagnetic sensor records vehicle wheel rotation number of turns n, thus can calculate the stroke S of bicycle:

S＝C×n＝2πr×n。

3. bicycle navigational system according to claim 2, is characterized in that: described Bus-Speed Monitoring module, is tested the speed by AMR geomagnetic sensor:

The magnet signal of two same characteristic features is detected by AMR geomagnetic sensor, and the sampling number N between these two magnet signal intensities cumulative, adopt the bicycle girth C calculated, then the speed of a motor vehicle computing formula of bicycle is as follows:

$V=\frac{C}{N\&times;T}$

In formula, T is the sampling period.

4. bicycle navigational system according to claim 1, is characterized in that: the attitude that described attitude detection module energy prompting bicycle is current, if initial time exists GPS supplementary module, can determine the traveling orientation of bicycle in real time:

When bicycle is in accurate stationary state, described accurate stationary state comprises static and at the uniform velocity state, and obtain bicycle initial state information by the output valve resolving accelerometer, described bicycle initial state information comprises pitching and roll information;

When bicycle is kept in motion, relies on gyro output valve to carry out bicycle posture renewal, and accelerometer can be used to assist gyroscopic drift compensation and attitude correction.

5. bicycle navigational system according to claim 4, is characterized in that:

The dynamic Attitude Algorithm flow process of bicycle is specially:

Before cycling, the drift of gyro is corrected, gathers bicycle gyro output valve under static state and accumulated samples is counted, the output valve of gyro is averaging:

$\mathrm{\&epsiv;}=\frac{\underset{i=1}{\overset{N}{\&Sigma;}}{\mathrm{\&omega;}}_i}{N}$

In formula, ε is gyroscopic drift, ω _ifor gyro output valve, N is sampling number;

Before cycling, use acceleration of gravity to calculate the attitude angle of bicycle in the projection components of three axis accelerometer, described attitude angle comprises the angle of pitch and roll angle:

$\left\{\begin{array}{c}\mathrm{\&theta;}=asin\frac{a_y}{\sqrt{a_x^2+a_y^2+a_z^2}}\\ \mathrm{\&gamma;}=asin\frac{a_x}{\sqrt{a_x^2+a_y^2+a_z^2}}\end{array}\right.$

In formula, θ is the angle of pitch, and γ is roll angle, a _x, a _yand a _zbe respectively the projection components of acceleration of gravity in three axis accelerometer;

Adopt hypercomplex number Attitude Algorithm to upgrade the attitude information of bicycle, wherein, the transformational relation of hypercomplex number and Eulerian angle is:

$\left\{\begin{array}{c}\mathrm{\&theta;}=a\tan \left(\frac{Q_0{Q}_1+Q_2{Q}_3}{1-2\left(Q_1^2+Q_2^2\right)}\right)\\ \mathrm{\&gamma;}=a\sin \left(Q_0{Q}_2-Q_3{Q}_1\right)\end{array}\right.$

In formula, Q is attitude quaternion, and θ is the angle of pitch, and γ is roll angle;

Accelerometer assists gyroscopic drift compensation and attitude correction algorithm flow:

Calculate the acceleration value a of each sampling instant bicycle, and to be stored in length be in N buffer zone:

$a=\sqrt{a_x^2+a_y^2+a_z^2}$

In formula, a _x, a _yand a _zbe respectively three axle components of accelerometer;

If the vector value a of current time acceleration meets | a-g| < λ, then centered by this puts, N number of acceleration value before and after storing, setting up a length is the data buffer of 2N+1, and calculates the standard deviation sigma (a) of acceleration value in data buffer;

If then think that bicycle is in accurate stationary state:

$\left\{\begin{array}{c}\mathrm{\&sigma;}\left(a\right)=\sqrt{\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{\left(a_i-\stackrel{\&OverBar;}{a}\right)}^2}{2N+1}}\\ \stackrel{\&OverBar;}{a}=\frac{\underset{i=1}{\overset{2N+1}{\mathrm{\&Sigma;}}}{a}_i}{2N+1}\end{array}\right.$

In formula, a _ifor the acceleration value in buffer zone;

If bicycle is in accurate stationary state, utilize the output valve of accelerometer to recalculate attitude, and reset the attitude information in the dynamic Attitude Algorithm of bicycle.

6. bicycle navigational system according to claim 1, it is characterized in that: when bicycle crashes, described collision detection module can preserve bicycle collision information, and described collision information comprises current speed and acceleration, and uploads to cloud server by mobile phone application.

7. bicycle navigational system according to claim 6, is characterized in that:

Bicycle collision detection modular algorithm flow process:

If the accekeration of bicycle forward direction is a, setting up length is that the buffer zone W store sample of m obtains forward acceleration;

After the data in the W of buffer zone obtain upgrading, detect it one by one and store data and whether be negative and the absolute value data number n that whether is greater than threshold epsilon and meets this condition continuously;

If n > is m/2, then think that bicycle and barrier there occurs collision;

Calculate the kinetic energy of bicycle when colliding to be expressed as follows:

$W=\frac{1}{2}{\mathrm{mV}}^2$

In formula, W is the kinetic energy of bicycle, and m is the quality of people and bicycle, speed when V is collision.

8. bicycle navigational system according to claim 1, is characterized in that: bicycle side looks through surveys modular algorithm flow process:

If the roll angle that dynamically gesture module exports is γ, setting up length is that the buffer zone W of m is to store the roll angle of current time;

After the data in the W of buffer zone obtain renewal, detect the number n whether its absolute value storing data is greater than threshold epsilon and meets this condition continuously one by one;

If n > is m/2, then think that bicycle there occurs rollover.

9. bicycle navigational system according to claim 1, it is characterized in that: stroke measurment module and Bus-Speed Monitoring module measure the current stroke of bicycle and velocity information respectively, the moment of cycling is started user, the alternate position spike score value using GPS former and later two moment of receiving end to export calculates the initial orientation of bicycle, gyro output valve constantly updates bicycle orientation, and the method for utilization dead reckoning can in real time output from the current position coordinates of driving.

10. bicycle navigational system according to claim 9, is characterized in that:

GPS information determination bicycle orientation algorithm flow:

Suppose that the initial orientation of bicycle is ψ ₀, utilize the output valve of gyro to upgrade attitude and the azimuth information of bicycle;

When bicycle is kept in motion, and when GPS chip receives signals clear is covered, the latitude and longitude information utilizing GPS chip to export, fix the position ψ;

$\mathrm{\&psi;}=atan\frac{\mathrm{\&Delta;}\mathrm{\&lambda;}}{\mathrm{\&Delta;}L}$

The orientation ψ utilizing GPS information measurement to obtain resets the orientation values in dynamic Attitude Algorithm, and upgrades attitude information:

In formula, θ is the angle of pitch, for roll angle, ψ is position angle, and Q is attitude quaternion;

Bicycle navigation algorithm flow:

By bicycle displacement according to current orientation travel direction cosine decomposition, project to east orientation and north orientation respectively, the traveling-position of bicycle can be determined:

$\left\{\begin{array}{c}{x}_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{sin\&psi;}}_i\\ y_n=\underset{i=0}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;y}}_i=\underset{i=0}{\overset{n}{\&Sigma;}}S{\mathrm{cos\&psi;}}_i\end{array}\right.$

In formula, S represents the girth of bicycle, ψ _irepresent the orientation of bicycle, x _nrepresent east orientation displacement, y _nrepresent north orientation displacement;

The bicycle position coordinates obtained is converted to latitude and longitude information, imports mobile phone A PP map software by bluetooth module, the current location of user can be shown in real time.