CN102538790A - Method for solving difference of gyroscope parameters in inertial navigation - Google Patents

Abstract

The invention provides a method for solving difference of gyroscope parameters in inertial navigation, which adopts an inertial navigation system and comprises the following steps: 1 respectively sampling gyroscope data, temperature sensor data, global position system (GPS) data and vehicle speed pulse signals; 2 calculating and obtaining angular acceleration after processing the gyroscope data and performing temperature compensation and further calculating a deviation angle; 3 analyzing the GPS data collected in the step 1 to obtain an original coordinate and an initial angle; 4 comparing the vehicle speed pulse signals collected in the step 1 with a vehicle speed corresponding table to obtain vehicle speed information and further obtaining displacement; and 5 performing fusion processing to the initial angle, the deviation angle, the displacement and original coordinate data which are calculated and obtained in the step2, the step 3 and the step 4, and reckoning coordinate information at the next moment. By means of the method, the problem of the difference of the gyroscope parameters in the inertial navigation system is solved.

Description

The otherness solution of gyroscope parameter in the inertial navigation

Technical field

The present invention relates to the inertial navigation technology field, particularly relate to a kind of inertial navigation technology, belong to the vehicle mounted guidance field based on gyroscope, GPS navigation equipment.

Background technology

The vehicle mounted guidance technology is modern multi-disciplinary new and high technology crystallization.It combines new and high technologies such as sensing technology, GIS digital and electronic ground diagram technology, city intelligent traffic technology, GSM dynamic navigation communications industry such as Navsat and target localization technology, gyroscope.

The built-in gps antenna of tradition onboard navigation system can receive from 3 data messages that transmitted in earth-circling 24 gps satellites at least; In conjunction with the electronic chart that is stored in the automatic navigator; The position coordinates of confirming through gps satellite signal is complementary therewith, confirms the accurate position of automobile in electronic chart.On the basis of location, can pass through multifunction display, best traffic route is provided, information such as the place ahead road conditions and nearest refuelling station, restaurant, hotel.Conventional navigation systems relies on GPS fully and navigates, and in the practical application, because of reasons such as urban canyons, underpass, overpass, dense jungles, gps signal is weakened or shields.Onboard navigation system can't normally receive gps signal, does not have coordinate information just can't mate with map datum, and onboard navigation system can't be navigated normally.

Vehicle-mounted inertial navigation system can solve because of gps signal weakens or shields and cause the problem that can't navigate.Inertial navigation system goes out its position of any down from the position of a known point according to carrier course angle that records continuously and speed calculation.

Along with the development of onboard navigation system, inertial navigation has played increasing effect in vehicle-mounted precision navigation.Traditional navigational system only is fixed against GPS and navigates and have a lot of blind spots.The first, be exactly weakening of gps signal.Influencing the factor that gps signal weakens has a lot, and at rainy weather, because cloud layer is too thick, the signal of GPS can weaken, and GPS does not receive the effective GPS signal and causes navigation to be lost efficacy.At the Lin Yin place, because dense leaf has blocked gps signal, the signal of GPS also has decay to a certain degree.The second, the shielding of gps signal.Navigational system can have no gps signal in through tunneling process, simultaneously, go out the tunnel after, have the blind area of certain hour, be the time of reorientating of GPS during this period of time.The 3rd, gps signal is invalid for navigation.Sometimes for gps system, gps signal has received effective signal, but signal is invalid for navigation.Parallel line for example, because civilian gps signal is the C/A sign indicating number, precision is a 100-10 rice, the distance between 2 parallel lines is lower than 10 meters and will causes locating inaccurate.GPS has signal in fact, for navigation, also can't accurately navigate to that route.Route is inaccurate will to cause the map match mistake, thereby navigation was lost efficacy.

These cause the factor of navigational system problem to possess unpredictability again.Can't know accurately that which when and where can take place, simple dependence GPS navigation system can't reach desirable effect.Even, rely on the navigation function that the navigational system of GPS has no merely in the specific occasion.

Gyroscope is a kind of angular motion pick-up unit.Gyroscope is with the angular motion pick-up unit of the responsive housing relative inertness of the momentum moment of high speed rotary body space around one or two axle that is orthogonal to the axis of rotation.Because the problem of gyrostatic manufacturing process, the very possible output at zero point of same batch gyroscope, that temperature is floated parameter is all different.This just need consider to use the algorithm of software and hardware to solve because the parameter inconsistency of the product that the problem of manufacturing process causes when volume production.

The inconsistency that output all can be arranged owing to the reason of the environment for use of PCB design, SMT technology, vehicle with a gyroscope.If the problem that these factors is not caused is handled, will cause when volume production, can't accomplishing the consistance of product parameters.Even with having the inconsistent problem that parameter appears in 2 starts in a vehicle-mounted inertial navigation set.

As the guide that shows the way in unknown highway section, stable and the accuracy of navigational system play very important effect.If navigation was lost efficacy, might cause the waste of time and resource.Inertial navigation system is as civilian precision navigation system, the high-precision new demand of automobile navigation of new generation under the potential competent new trend.

Relevant explanation of nouns:

1, the abbreviation of ADC:Analog-to-Digital Converter is to be the switching device of digital signal with analog signal conversion.

2, GIS:Geographic Information System, GIS-Geographic Information System.

3, GSM:Global System for Mobile Communications, global system for mobile communications.

4, GPS:Global Positioning System, GPS.

5, API:Application Programming Interface, API.

Summary of the invention

The present invention overcomes the problem of gyroscope zero point drift and temperature drift, has solved the gyroscope otherness, and the otherness solution of gyroscope parameter in a kind of inertial navigation is provided.

This method realizes based on hardware device; The otherness solution of gyroscope parameter in the inertial navigation; Adopt inertial navigation system, comprise gyroscope, temperature sensor, gps receiver, vehicle speed pulse signal acquisition circuit and flush bonding processor, method may further comprise the steps:

Step 1, respectively gyro data, temperature sensor data, gps data, vehicle speed pulse signal are sampled;

Step 2, to gyro data handle and temperature compensation after, calculate angular acceleration, and then calculate deviation angle;

Step 3, the gps data that collects in the step 1 is resolved, obtain original coordinates and initial angle;

Step 4, vehicle speed pulse signal of gathering in the step 1 and speed of a motor vehicle correspondence table are compared, obtain speed information, and then obtain displacement;

Step 5, initial angle, deviation angle, displacement, original coordinates data that step 2 is calculated in the step 4 are carried out fusion treatment; Extrapolate next coordinate information constantly, go out any position of its time from the position of a known point according to carrier course angle that records continuously and speed calculation. thereby can measure the current location of movable body continuously.

Preferably, above-mentioned steps one specifically may further comprise the steps:

1.1) voltage data of gyroscope output is sampled, and the data that sample are carried out boundary value processing and mean filter processing;

1.2) data of reading temperature sensor, and the temperature sensor data are carried out the boundary value processor is handled and mean filter is handled;

1.3) read the data of GPS receiver, and data are carried out decoding processing, be stored in the internal storage location of appointment;

1.4) read the vehicle speed pulse value, and number of pulses is according to carrying out pre-service.

Preferably, above-mentioned steps two specifically may further comprise the steps:

2.1) data and the gyrostatic raw data of temperature sensor imported in the bivariate table, calculate the gyro data after the temperature compensation;

2.2) to the go forward side by side gyro data of trip temperature compensation of sampling repeatedly, utilize Kalman filtering and weight moving average algorithm computation to go out angular acceleration;

2.3) angular velocity is calculated deviation angle to time integral.

Preferably, above-mentioned steps three specifically may further comprise the steps:

3.1) gps data is decoded, obtain the data in coordinate data section and the angle-data section;

3.2) coordinate data section and angle-data section are decoded as 16 system data, and be stored in the structure.

Preferably, above-mentioned steps four specifically may further comprise the steps:

4.1) the vehicle speed pulse signal and the speed of a motor vehicle correspondence table of gathering are compared, obtain speed information;

4.2) displacement of speed information being obtained current time to time integral.

Preferably, above-mentioned steps five specifically may further comprise the steps:

5.1) utilize initial angle and deviation angle to calculate the current actual angle of equipment;

5.2) actual angle, displacement and original coordinates data are carried out fusion treatment, extrapolate next coordinate information constantly.

Preferably, above-mentioned steps 1.1)-1.4) accomplish through flush bonding processor.

Preferably, the otherness solution of gyroscope parameter in the above-mentioned inertial navigation is characterized in that: said gps data is the NEMA form.

Through this method, solved gyroscope parameter variability issues in the inertial navigation system.

Vehicle-mounted inertial navigation operates on the hardware platform, realizes intelligent inertial navigation.Major function with following aspect:

1. show zero point drift from NMO correction;

2. realize the parametric compensation that temperature is floated;

3. start is from NMO correction gyroscope parameter;

4. accurately dead reckoning of intelligence, with respect to traditional navigational system based on GPS, this system have very weak at gps signal or situation about not having under, realize precision navigation;

5. collecting vehicle information, vehicle-mounted inertial navigation system can also be collected the information of vehicle, the performance and the situation of the monitoring vehicle of intelligence.And these information are diagnosed and analyze.Give navigational system with these information indicatings at last.

Description of drawings

Fig. 1 is a schematic flow sheet of the present invention;

Fig. 2 is a system hardware general structure block diagram;

Fig. 3 is the software section system architecture diagram;

Fig. 4 is an idiographic flow synoptic diagram of the present invention.

Embodiment

Understand and embodiment of the present invention for the ease of those of ordinary skills, the present invention is made further detailed description below in conjunction with accompanying drawing and embodiment.

As shown in Figure 1, be operating process of the present invention, adopt inertial navigation system, comprise gyroscope, temperature sensor, gps receiver, vehicle speed pulse signal acquisition circuit and flush bonding processor.As shown in Figure 3, software section is divided into hardware layer, hardware abstraction layer, system call layer, application layer.Hardware layer is described concrete hardware register and interface; Hardware abstraction layer is the interface of hardware layer and application layer; To be abstracted into the API that application layer can directly be called to the concrete operation of hardware, the system call layer distributes the resource in the system, and task is dispatched.May further comprise the steps:

Step 1, respectively gyro data, temperature sensor data, gps data, vehicle speed pulse signal are sampled, this step specifically comprises:

1.1) flush bonding processor uses ADC that the voltage data of gyroscope output is sampled, and the data that ADC samples are carried out boundary value is handled and mean filter is handled;

1.2) data of flush bonding processor through the digital interface reading temperature sensor, and the temperature sensor data are carried out boundary value processor mean filter handle;

1.3) flush bonding processor reads the NEMA formatted data of GPS receiver through digital interface, and data are carried out decoding processing, be stored in the internal storage location of appointment;

1.4) flush bonding processor reads the vehicle speed pulse value through pulse acquisition circuit, and number of pulses is according to carrying out pre-service.

Step 2, to gyro data handle and temperature compensation after, utilize Kalman filtering and weight moving average algorithm computation to obtain angular acceleration, then angular acceleration is calculated deviation angle to time integral; This step specifically comprises:

2.1) data and the gyrostatic raw data of temperature sensor imported in the bivariate table, calculate the gyro data after the steady compensation.

α _gyro＝A[X _temper，Y _{gyro_adc}]

In the formula,

α _Gyro: gyrostatic angular acceleration.

X _Temperature: temperature sensor output.

Y _{Gyro_adc}: the raw data that gyroscope ADC gathers.

2.2) to the go forward side by side gyro data of trip temperature compensation of sampling repeatedly, utilize Kalman filtering that gyro data is carried out Filtering Processing.Concrete Kalman filtering step is following, and the state equation of the discrete system of Kalman filtering with the measurement equation is:

X _k＝φ _k，k-1X _k-1+Γ _k-1W _k-1 (2-1)

Z _k＝H _kX _k+V _k

X in the formula _kBe k n dimension state vector constantly, it comprises angle, angular velocity, and angular acceleration, these three amounts are divided into direct north and due east direction again, and six components are promptly arranged; Z _kFor k m dimension is constantly measured vector.DR is carried out filtering, and then measured value is angular acceleration and speed; φ _{K, k-1}Be the step transition matrix (n * n rank) of k-1 to the k moment; W _K-1Be k-1 system noise vector (r dimension) constantly; Γ _K-1Be system noise matrix (n * r rank) that its expression is influenced the degree of each state respectively to k each noise constantly by k-1; H _kBe k measurement matrix (m * n rank) constantly; V _kBe k m dimension measurement noise vector constantly.(6-1) resolves to equation, requires { W _kAnd { V _kBe mutual incoherent zero-mean white noise sequence, have:

E{W _k}＝0 $E\left\{W_k{W}_j^T\right\}=Q_k{\mathrm{\δ}}_{\mathrm{kj}}$

E{V _k}＝0 $E\left\{V_k{V}_j^T\right\}=R_k{\mathrm{\δ}}_{\mathrm{kj}}$

In the formula: Q _kBe called the system noise variance matrix; R _kBe called and measure the noise variance matrix;

In the Kalman filtering process, require both known, and Q _kBe nonnegative definite battle array, R _kBe positively definite matrix.δ _KjBe Kronec ker δ function, promptly

${\mathrm{\δ}}_{\mathrm{kj}}=\left\{\begin{array}{c}0,k\≠j\\ 1,k=j\end{array}\right.$

Specify below the state equation of DR filtering formed: the observed reading that we the choose vehicle that to be gyrostatic output

export with vehicle speed pulse in the sampling period T time, advance apart from s.The measurement vector that is system can be written as following form for

each amount wherein:

In the formula,

ε _∧, ε _∨---the constant value drift and the random drift of gyro;

δ _∨---the measuring error of mileometer.

Measurement equation to DR carries out discretize:

Utilize the expansion of Taylor series,, keep single order in a small amount, its discretize is had through great amount of calculation:

$H\left(k\right)=\left[\begin{array}{cccccc}0& h_1& h_2& 0& h_3& h_4\\ 0& h_5& 0& 0& h_6& 0\end{array}\right]$

Wherein,

$h_1=\frac{{\hat{a}}_n(k,k-1){{\hat{v}}^2}_e(k,k-1)-2{\hat{v}}_e(k,k-1){\hat{v}}_n(k,k-1){\hat{a}}_e(k,k-1)-{\hat{a}}_n(k,k-1){{\hat{v}}_n}^2(k,k-1)}{{[{v_n}^2(k,k-1)+{v_e}^2(k,k-1)]}^2}$

$h_2=\frac{{\hat{v}}_n(k,k-1)}{{\hat{v}}_n^2(k,k-1)+{\hat{v}}_e^2(k,k-1)}$

$h_3=\frac{{\hat{a}}_e(k,k-1){\hat{v}}_e^2(k,k-1)-2{\hat{v}}_e(k,k-1){\hat{v}}_n(k,k-1){\hat{a}}_n(k,k-1)-{\hat{a}}_e(k,k-1){{\hat{v}}_n}^2(k,k-1)}{{[{v_n}^2(k,k-1)+{v_e}^2(k,k-1)]}^2}$

$h_4=\frac{{\hat{v}}_e(k,k-1)}{{\hat{v}}_n^2(k,k-1)+{\hat{v}}_e^2(k,k-1)}$

$h_5=\frac{T\·{\hat{v}}_e(k,k-1)}{\sqrt{{\hat{v}}_n^2(k,k-1)+{\hat{v}}_e^2(k,k-1)}}$

$h_6=\frac{T\·{\hat{v}}_n(k,k-1)}{\sqrt{{\hat{v}}_n^2(k,k-1)+{\hat{v}}_e^2(k,k-1)}}$

These values can obtain from

, thereby calculate the value of H (K).

State one-step prediction equation:

${\hat{X}}_{k/k-1}={\mathrm{\φ}}_{k,k-1}{\hat{X}}_{k-1}$

The state estimation equation:

${\hat{X}}_k={\hat{X}}_{k/k-1}+K_k(Z_k-H_k{\hat{X}}_{k/k-1})$

The filter gain equation:

$K_k=P_{k/k-1}{H}_k^T{(H_k{P}_{k/k-1}{H}_k^T+V_k)}^{-1}$

One-step prediction square error equation:

$P_{k/k-1}={\mathrm{\φ}}_{k,k-1}{P}_{k-1}{\mathrm{\φ}}_{k,k-1}^T+W_{k-1}$

Estimate the square error equation:

P _k＝(I-K _kH _k)P _k/k-1

Or $P_k=(I-K_k{H}_k)P_{k/k-1}{(I-K_k{H}_k)}^T+K_k{V}_k{K}_k^T$

The setting of initial value: in the process of Kalman filtering, need to set X (0) and P (0).General P (0) can not be set to 0, can be set to other constant.

Carry out Kalman filtering according to above-mentioned equation.

2.3) utilize the weight moving average algorithm computation to go out angular acceleration;

$\stackrel{\‾}{Q}=\underset{t=1}{\overset{n}{\mathrm{\Σ}}}\frac{Q_t{W}_t}{\mathrm{\Σ}{W}_t}$

In the formula,

: weighted mean.

Q _t: certain unit interval sampled value.

W _t: t unit interval sampling flexible strategy.

N: total number of samples.

2.3) angular velocity is calculated deviation angle to time integral.

Step 3, the gps data that collects in the step 1 is resolved, obtain coordinate information and original angle information, this step specifically comprises:

3.1) gps data is decoded through the NEMA form, obtain the data in coordinate data section and the angle-data section;

3.2) coordinate data section and angle-data section are decoded as 16 system data, and be stored in the structure.

Step 4, vehicle speed pulse signal of gathering in the step 1 and speed of a motor vehicle correspondence table are compared, obtain speed information, speed information is obtained the displacement of current time to the car time integral, this step specifically comprises:

4.1) the vehicle speed pulse signal and the speed of a motor vehicle correspondence table of gathering are compared, obtain speed information;

4.2) displacement of speed information being obtained current time to time integral.

Step 5, initial angle, deviation angle, displacement, original coordinates data that step 2 is calculated in the step 4 are carried out fusion treatment, extrapolate next coordinate information constantly.This step specifically comprises:

5.1) utilize initial angle and deviation angle to calculate the current actual angle of equipment; Actual angle, displacement and original coordinates data are carried out fusion treatment, extrapolate next coordinate information constantly.

X _t＝SIN(θ+Δθ)×l+X _t-1

Y _t＝COS(θ+Δθ)×l+Y _t-1

X _t: next X axial coordinate value constantly.

Y _t: next Y axial coordinate value constantly.

θ: the angle of current time.

Δ θ: the side-play amount of current angle.

X _T-1: the X axial coordinate value in a last moment.

Y _T-1: the Y axial coordinate value in a last moment.

Wherein, hardware device is specifically as shown in Figure 2, and hardware system adopts ARM+GPS+ gyroscope+vehicle data Acquisition Circuit+temperature sensor framework; Wherein ARM is mainly used in data acquisition, algorithm computing and communication, and GPS is used to receive the gps satellite data, the angular acceleration that gyroscope is used for checking vehicles; The vehicle data Acquisition Circuit is used for the speed of a motor vehicle of collection vehicle; Lampet, forward/backward drives to wait signal.Temperature sensor is used for measuring gyrostatic environment temperature.

As shown in Figure 4, for idiographic flow synoptic diagram of the present invention, can learn concrete method step through this process flow diagram, comprising:

Step 1, respectively gyroscope, temperature sensor, GPS, vehicle speed pulse signal are sampled;

1.1 flush bonding processor uses ADC that the voltage data of gyroscope output is sampled, and will

The data that ADC samples are carried out the boundary value processing and mean filter is handled;

1.1.1 adc data GYRO_DAT_ADC is carried out boundary value to be handled.

If GYRO_DAT_ADC gives up this value greater than the boundary value GYRO_ADC_LIMIT_UP that is provided with or less than the boundary value GYRO_ADC_LIMIT_DOWN that is provided with.

1.1.2 the effective value of GYRO_DAT_ADC of N sampling is sued for peace, asks its average GYRO_DAT then.

1.2 flush bonding processor passes through the data of digital interface reading temperature sensor, and the temperature sensor data is carried out boundary value processor mean filter handle;

1.2.1 data TEMPER_DAT is carried out boundary value to be handled.

If TEMPER_DAT gives up this value greater than the boundary value TEMPER_LIMIT_UP that is provided with or less than the boundary value TEMPER_LIMIT_DOWN that is provided with.

1.2.2 the effective value of TEMER_DAT of N sampling is sued for peace, asks its average GYRO_DAT then.

1.3 flush bonding processor reads the NEMA formatted data of GPS receiver through digital interface, and data are carried out decoding processing, is stored in the internal storage location of appointment;

1.4 flush bonding processor reads the vehicle speed pulse value through pulse acquisition circuit, and inquires corresponding vehicle speed value according to the vehicle speed pulse correspondence table;

After step 2, the gyro data that will handle are carried out temperature compensation, utilize Kalman filtering and weight moving average algorithm to obtain angular acceleration, then angular acceleration is calculated deviation angle to time integral;

2.1 the data and the gyrostatic raw data of temperature sensor are imported in the bivariate table, calculate the gyro data after the temperature compensation;

The gyro data of trip temperature compensation utilizes Kalman filtering and weight moving average algorithm computation to go out angular acceleration 2.2 go forward side by side to repeatedly sampling;

2.3 angular velocity is calculated deviation angle to time integral;

Step 3, the gps data that collects in the step 1 is resolved, obtain coordinate information and original angle information;

3.1 gps data is decoded through the NEMA form, obtain the data in coordinate data section and the angle-data section;

3.2 coordinate data section and angle-data section are decoded as 16 system data, and are stored in the structure;

Step 4, vehicle speed pulse signal of gathering in the step 1 and speed of a motor vehicle correspondence table are compared, obtain speed information, speed information is obtained the displacement of current time to the car time integral;

4.1 the vehicle speed pulse signal and the speed of a motor vehicle correspondence table of gathering are compared, obtain speed information;

4.2 speed information is obtained the displacement of current time to time integral;

Step 5, initial angle, deviation angle, displacement, original coordinates data that step 2 is calculated in the step 4 are carried out fusion treatment, extrapolate next coordinate information constantly.

Calculate the current actual angle of equipment 5.1 utilize initial angle and deviation angle;

5.2 actual angle, displacement and original coordinates data are carried out fusion treatment, extrapolate next coordinate information constantly;

The above; Only be in order to practical implementation case of the present invention to be described; But be not in order to limit practical range of the present invention; Such as those skilled in the art must be covered by the scope of claim of the present invention not breaking away from all equivalence changes of being accomplished under indicated spirit of the present invention and the principle or modifying.

Claims (8)

1. the otherness solution of gyroscope parameter in the inertial navigation adopts inertial navigation system, comprises gyroscope, temperature sensor, gps receiver, vehicle speed pulse signal acquisition circuit and flush bonding processor, it is characterized in that may further comprise the steps:

Step 1, respectively gyro data, temperature sensor data, gps data, vehicle speed pulse signal are sampled;

Step 2, to gyro data handle and temperature compensation after, calculate angular acceleration, and then calculate deviation angle;

Step 3, the gps data that collects in the step 1 is resolved, obtain original coordinates and initial angle;

Step 4, vehicle speed pulse signal of gathering in the step 1 and speed of a motor vehicle correspondence table are compared, obtain speed information, and then obtain displacement;

Step 5, initial angle, deviation angle, displacement, original coordinates data that step 2 is calculated in the step 4 are carried out fusion treatment, extrapolate next coordinate information constantly.

2. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 1, it is characterized in that: said step 1 specifically may further comprise the steps:

1.1) voltage data of gyroscope output is sampled, and the data that sample are carried out boundary value processing and mean filter processing;

1.2) data of reading temperature sensor, and the temperature sensor data are carried out the boundary value processor is handled and mean filter is handled;

1.3) read the data of GPS receiver, and data are carried out decoding processing, be stored in the internal storage location of appointment;

1.4) read the vehicle speed pulse value, and number of pulses is according to carrying out pre-service.

3. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 1, it is characterized in that: said step 2 specifically may further comprise the steps:

2.1) data and the gyrostatic raw data of temperature sensor imported in the bivariate table, calculate the gyro data after the temperature compensation;

2.2) to the go forward side by side gyro data of trip temperature compensation of sampling repeatedly, utilize Kalman filtering and weight moving average algorithm computation to go out angular acceleration;

2.3) angular velocity is calculated deviation angle to time integral.

4. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 1, it is characterized in that: said step 3 specifically may further comprise the steps:

3.1) gps data is decoded, obtain the data in coordinate data section and the angle-data section;

3.2) coordinate data section and angle-data section are decoded as 16 system data, and be stored in the structure.

5. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 1, it is characterized in that: said step 4 specifically may further comprise the steps:

4.1) the vehicle speed pulse signal and the speed of a motor vehicle correspondence table of gathering are compared, obtain speed information;

4.2) displacement of speed information being obtained current time to time integral.

6. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 1, it is characterized in that: said step 5 specifically may further comprise the steps:

5.1) utilize initial angle and deviation angle to calculate the current actual angle of equipment;

5.2) actual angle, displacement and original coordinates data are carried out fusion treatment, extrapolate next coordinate information constantly.

7. the otherness solution of gyroscope parameter in the inertial navigation as claimed in claim 2 is characterized in that: said step 1.1)-1.4) accomplish through flush bonding processor.

8. like the otherness solution of gyroscope parameter in claim 2 or the 4 described inertial navigations, it is characterized in that: said gps data is the NEMA form.

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