CN101858980A - Intelligent hypercompact combination navigation method of vehicle-mounted GPS software-based receiver - Google Patents

Abstract

The invention discloses an intelligent hypercompact combination navigation method of a vehicle-mounted GPS software-based receiver, which carries out switching of the intelligent navigation work mode, self-adaptive matching of multi-source system, filter and intelligent navigation positioning against for the hypercompact combination mode of a software GPS (global satellite positioning system) receiver/low cost MINS (Micro Inertia Navigation System). Whether in the high dynamic environment or in the weak satellite signal environment, the method can adequately utilize the information obtained by the subsystems, can intelligently allocate the main system, the auxiliary system and the combination form thereof, can instantly correct and compensate the error, and can effectively realize the vehicle-mounted seamless positioning of the urban traffic.

Description

A kind of vehicle-mounted intelligent hypercompact combination navigation method based on the GPS software receiver

Technical field

The present invention is applicable to the technical field of navigation and positioning of low accuracy requirement in urban transportation, the navigation etc., it is navigator fix requirement in order to reach high precision, high reliability and to locate coverage greatly, the intelligent hypercompact combination navigation technology of itself and low-cost inertial sensor of research has realized the vehicle-mounted seamless location in the faint and high dynamic dispatching environment of satellite-signal on the basis of GPS software receiver.

Background technology

Inertial navigation is a kind of any external information that do not rely on, the also outside self-aid navigation system of emittance not, have that maneuverability is good, environment-adapting ability by force, advantage of high precision in short-term.Yet because the error of inertial navigation system is accumulated in time, navigation accuracy is dispersed in time, can't work long hours separately.The GPS navigation system realizes navigation, the good stability that works long hours, easy to use, with low cost by receiving satellite signal.But when carrier is done the high-speed maneuver campaign, the sign indicating number ring of receiver and the easy losing lock of carrier wave ring and lossing signal, and at gps signal " blind area " as city tunnel, zone that skyscraper is intensive can't position because signal blocks or multipath disturbs or bearing accuracy poor.

This shows that for satisfying high precision, high reliability, big location coverage navigation request that environment-adapting ability is strong, best approach combines multiple navigational system exactly, reaches the purpose of learning from other's strong points to offset one's weaknesses.The GPS/INS integrated navigation has three kinds of integrated modes at present usually, i.e. pine combination, tightly combination and hypercompact combination.The common ground of three kinds of patterns all is to provide minimum variance estimate by information fusion technology to the inertial navigation system error, utilizes the estimated value of error to go to revise inertial navigation system then.And hypercompact combination is darker than the above two combined level, it utilizes the position and speed information of INS and GPS receiver tracking ring to carry out information fusion, can overcome the contradiction aspect the receiver tracking bandwidth and squelch in the dynamic applied environment of height, strengthen its antijamming capability.

Eighties of last century begins the seventies, a lot of external research institutions all are devoted to the integrated navigation Study on Technology, aerospace system research institute as the Blang Shi Weige University of Science and Technology of Germany, to tightly make up by Kalman filtering based on the inertial measurement cluster and the GPS of solid state sensor, strengthened the reliability of miniature aviation aircraft system; The integrated navigation system that is combined by laser gyro inertia system, air data sensor and GPS receiver is developed in U.S. Honeywell company and Stanford Telecommunications Incorporations cooperation.And the ratio of domestic starting in this respect is later, much is only limited to laboratory study, but has also developed some engineering systems.

Yet present integrated navigation system algorithm is triangular web with auxiliary another system of same pattern, and variation intelligently can't conform.And make a general survey of the vehicle-mounted satellite navigation product of China, and generally being based on and developing on the OEM plate base of GPS, therefore gordian technique and nucleus module have certain limitation all from abroad in the application of product.In order to make full use of present navigation resource,, be necessary they are made up and research and develop low-cost vehicle intelligent integrated navigation algorithm along with the development of Satellite Software reception technique, low-cost inertial technology to realize vehicle-mounted seamless navigation.

Summary of the invention

Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, a kind of new vehicle-mounted intelligent hypercompact combination navigation method based on the GPS software receiver is provided, the shortcoming that this method has overcome traditional single navigational system can not accurately locate for a long time because signal blocks or error is accumulated in time, and take the switching of intelligent navigation mode of operation, multi-source system Adaptive matching, filtering and intelligent navigation positioning and optimizing algorithm, provide that coverage is bigger, the higher also more accurate localization service of reliability.

The present invention adopts following technical scheme for achieving the above object:

A kind of vehicle-mounted intelligent hypercompact combination navigation method based on the GPS software receiver of the present invention may further comprise the steps:

(1), and, comprises gps signal carrier-to-noise ratio, visual star number amount, I, Q information, pseudorange pseudorange rates information and velocity location information with satellite-signal parsing generation GPS navigation data by GPS software receiver receiving satellite signal;

(2) gather inertial navigation data by the inertial navigation unit, and inertial navigation data is resolved formation speed positional information, I, Q information and pseudorange pseudorange rates information;

(3) according to above-mentioned data select the navigation main system and with the array mode of backup system, constitute the Kalman filtering subsystem;

(4) utilize EKF that described GPS navigation data, MINS inertial navigation data are carried out data fusion in senior filter, generate navigation data;

(5) the output navigation information is the described navigation data of step (4).

Preferably, in the described step (3), select the navigation main system and be with the method for backup system array mode:

(a) according to gps signal carrier-to-noise ratio, visual star number amount to judge the signal quality of GPS;

(b) according to the speed of carrier to judge whether being high dynamic environment;

When (c) non-high dynamic environment and gps signal were strong, selection MINS was a main system, carried out the pine combination with gps system, carried out data fusion to proofread and correct MINS in Kalman's senior filter, did not use the Kalman filtering subsystem;

When (d) non-high dynamic environment and gps signal were weak, selection MINS was a main system, tightly made up with gps system, and the pseudorange pseudorange rates information that is about to the two output is carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

(e) non-high dynamic environment and when being the gps signal blind area, selection MINS is a main system, carries out hypercompact combination with gps system, the I, the Q information that are about to the two output are carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

(f) in the high dynamic environment, selection GPS is a main system, carries out hypercompact combination with MINS, and the I, the Q information that are about to the two output are carried out data fusion to proofread and correct GPS in the Kalman filtering subsystem.

Preferably, described step (4) generates final navigation data for the velocity location information of MINS and GPS output merges to proofread and correct main system in senior filter.

Preferably, judge that according to gps signal carrier-to-noise ratio, visual star number amount the gps signal method for quality is as follows in the described step (a): if carrier-to-noise ratio more than or equal to 35dB/Hz and visual star number amount more than or equal to 4, then gps signal is strong; If carrier-to-noise ratio more than or equal to 20dB/Hz and less than 35dB/Hz and visual star number amount more than or equal to 4, then gps signal is medium; If carrier-to-noise ratio less than 4, then is the gps signal blind area less than 20dB/Hz or number of satellites.

Preferably, in the described step (b) according to the speed of carrier judge whether into the method for high dynamic environment as follows: when bearer rate during, be high dynamic environment,, be non-high dynamic environment when bearer rate during less than 100m/s more than or equal to 100m/s.

The present invention's advantage compared with prior art is:

(1) sample GPS software receiver and low-cost inertial sensor of the present invention realized simply, with low cost, is easy to optimize;

(2) the present invention can intelligence be switched navigation mode of operation and information fusion algorithm, and, autonomy-oriented humanized than the navigational system of other single integrated modes more rationally utilize the navigation information resource, and accommodative ability of environment is strong;

The present invention utilizes the position and speed information of MINS and GPS software receiver tracking loop to carry out hypercompact information fusion, can overcome the limitation that dynamically reaches single navigational system in the applied environment of feeble signal at height, strengthen its antijamming capability, effectively improved bearing accuracy.The present invention can be according to the primary/secondary system of the autonomous selection of working environment, and merge synchronous navigation data, more reasonably use EKF, obtain arbitrary subsystem, the wider also more stable new-type hypercompact combination navigation method of navigation coverage that a kind of precision is better than construction system.Thereby overcome the shortcoming that the GPS location technology is depended on satellite-signal unduly, also solved the problem that the MINS positioning error accumulates in time, can't locate separately for a long time.

Description of drawings

Fig. 1 is an algorithm flow chart of the present invention;

Fig. 2 is an embodiment of the invention principle schematic.

Embodiment

Be elaborated below in conjunction with the technical scheme of accompanying drawing to invention:

As shown in Figure 1, the present invention is based on software GPS receiver/hypercompact mode of operation of low-cost inertia, according to the autonomous reconstruct combined method of varying environment, make full use of the vehicle-mounted seamless location that limited navigation data is realized high precision, high reliability, concrete steps are as follows:

(1) receiving satellite signal, and resolve generation GPS navigation data

By the GPS software receiver, obtain signal carrier-to-noise ratio, visual star number amount, I, Q information, pseudorange pseudorange rates information and velocity location information;

(2) gather and resolve inertial navigation data

By the inertial navigation unit, obtain the velocity location information of carrier, and calculate pseudorange pseudorange rates information and I, Q information, method is as follows:

The real time position of note MINS is (x _Iy _Iz _I) ^T, the satellite real time position that is calculated by satellite ephemeris is (x _Gy _Gz _G) ^T, can get the real-time pseudorange information ρ of MINS position _IBy MINS to gps satellite S _jPseudorange ρ _IjCan be expressed as follows:

${\mathrm{\ρ}}_{\mathrm{Ij}}={[{(x_I-x_{\mathrm{Gj}})}^2+{(y_I-y_{\mathrm{Gj}})}^2+{(z_I-z_{\mathrm{Gj}})}^2]}^{\frac{1}{2}}---\left(1\right)$

The coordinate true value of supposing the receiver position is (x y z) ^T, then with formula (1) at (x y z) ^TThe place carries out the single order Taylor expansion:

${\mathrm{\ρ}}_{\mathrm{Ij}}={[{(x-x_{\mathrm{Gj}})}^2+{(y-y_{\mathrm{Gj}})}^2+{(z-z_{\mathrm{Gj}})}^2]}^{\frac{1}{2}}+\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂x}\mathrm{\δx}+\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂y}\mathrm{\δy}+\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂z}\mathrm{\δz}---\left(2\right)$

Utilize the symbol replacement, note

${[{(x-x_{\mathrm{Gj}})}^2+{(y-y_{\mathrm{Gj}})}^2+{(z-z_{\mathrm{Gj}})}^2]}^{\frac{1}{2}}=r_j---\left(3\right)$

So note

$\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂x}=\frac{(x-x_{\mathrm{Gj}})}{{[{(x-x_{\mathrm{Gj}})}^2+{(y-y_{\mathrm{Gj}})}^2+{(z-z_{\mathrm{Gj}})}^2]}^{\frac{1}{2}}}=\frac{(x-x_{\mathrm{Gj}})}{r_j}{=e}_{j1},\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂y}=\frac{(y-y_{\mathrm{Gj}})}{r_j}=e_{j2},\frac{\∂{\mathrm{\ρ}}_{\mathrm{Ij}}}{\∂z}=\frac{(z-z_{\mathrm{Gj}})}{r_j}=e_{j3}---\left(4\right)$

Then formula (1) can be reduced to

ρ _Ij＝r _j+e _j1δx+e _j2δy+e _j3δz (5)

But can get the pseudorange of MINS thus to every TV star.

The real-time position information of MINS output can be expressed as true value and error sum, promptly

Then MINS is to gps satellite S _jPseudorange rates be

But can get the pseudorange rates of MINS thus to every TV star.

I, the Q value of MINS prediction are produced by following formula, wherein ω _eAnd φ _eBe respectively predicted frequency sum of errors phase error, A is the amplitude of signal, and T is the cycle of filtering, and k is that the note in cycle is inferior

Wherein,

${\mathrm{\ω}}_e=\frac{\mathrm{\ω}}{c}|v_u-\widehat{v_u}|=\frac{\mathrm{\ω}}{c}{v}_e---\left(10\right)$

ω is the local frequency of carrier signal that produces, and c is the light velocity, R _uAnd v _uBe respectively the physical location and the speed data that receive,

With

Be respectively theoretical Position And Velocity data.R _eAnd v _eBe respectively the Position And Velocity error of MINS output, t is for calculating the time of this error.Can get I, the Q value of MINS thus to every satellite prediction.

(3) according to above-mentioned data select the navigation main system and with the array mode of backup system, constitute the Kalman filtering subsystem.Difference according to the integrated navigation pattern, the input of GPS/MINS Kalman subfilter is as follows respectively: during loose integrated mode, be input as bearer rate, position, attitude information that bearer rate, position, temporal information and inertial navigation system that the GPS software receiver calculates calculate, promptly among the figure 1. shown in; During tight integrated mode, be input as pseudorange, pseudorange rates information that pseudorange, pseudorange rates information and MINS that the GPS software receiver obtains dope according to bearer rate, position and gps satellite ephemeris, promptly among the figure 2. shown in; During hypercompact integrated mode, be input as I, Q information that I, Q information and MINS that the GPS software receiver obtains dope according to bearer rate, position and gps satellite ephemeris.Through after the filtering,, respectively the inertial error Compensation Feedback is given the MINS system or I, Q error compensation are fed back to the GPS navigation system according to the difference of selecting principle navigation system.At last, with principle navigation system resolve navigation information with carry out pine combination through the navigation information that obtains after the subfilter filtering, handle the back by Kalman's senior filter and export final navigation data.

Select the navigation main system and be with the step of backup system array mode:

1. according to gps signal carrier-to-noise ratio, visual star number amount judging the signal quality of GPS, if carrier-to-noise ratio more than or equal to 35dB/Hz and visual star number amount more than or equal to 4, then gps signal is strong; If carrier-to-noise ratio more than or equal to 20dB/Hz and less than 35dB/Hz and visual star number amount more than or equal to 4, a little less than then gps signal is; If carrier-to-noise ratio less than 4, then is the gps signal blind area less than 20dB/Hz or number of satellites.

2. according to the speed of carrier judging whether being high dynamic environment, when bearer rate during, be high dynamic environment more than or equal to 100m/s.

When 3. non-high dynamic environment and gps signal were strong, selection MINS was a main system, carried out the pine combination with gps system, did not use the Kalman filtering subsystem;

When 4. non-high dynamic environment and gps signal were medium, selection MINS was a main system, tightly made up with gps system, and the pseudorange pseudorange rates information that is about to the two output is carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

5. non-high dynamic environment and when being the gps signal blind area, selection MINS is a main system, carries out hypercompact combination with gps system, the I, the Q information that are about to the two output are carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

6. in the high dynamic environment, selection GPS is a main system, carries out hypercompact combination with MINS, and the I, the Q information that are about to the two output are carried out data fusion to proofread and correct GPS in the Kalman filtering subsystem.

17 dimension state vectors of tight integrated kalman filter subsystem are made up of the various error states of integrated navigation system, be respectively the error of the position of MINS on three directions, speed, attitude, accelerometer biasing, gyroscopic drift, and with the distance error of GPS receiver clock error equivalence, with the equivalence of GPS receiver clock frequency error apart from the rate error.Error state equation and the GPS error state equation of MINS are merged, can obtain the state equation of subsystem under tight integrated mode, be designated as

Wherein, X _I, X _GBe respectively the state vector of MINS and GPS, F _I, F _GBe respectively the system state matrix of MINS and GPS, G _I, G _GBe respectively the noise matrix of MINS and GPS, W _I, W _GBe respectively the system noise vector of MINS and GPS.The MINS that pseudorange, pseudorange rates and the step (2) that obtains according to GPS software receiver parsing in the step (1) obtains can get the measurement equation of tight integrated kalman filter subsystem to pseudorange, the pseudorange rates of gps satellite, is designated as

Wherein Z is a measuring value, and H is for measuring matrix, and X is total state vector, and V is an observation noise, note

H _ρ＝[H _ρ1?0 _4×12?H _ρ2] _4×17， $H_{\mathrm{\ρ}1}=\left[\begin{array}{ccc}{a}_{11}& a_{12}& a_{13}\\ a_{21}& a_{22}& a_{23}\\ a_{31}& a_{32}& a_{33}\\ a_{41}& a_{42}& a_{43}\end{array}\right],$ $H_{\mathrm{\ρ}2}=\left[\begin{array}{cc}1& 0\\ 1& 0\\ 1& 0\\ 1& 0\end{array}\right]$

$\left.\begin{array}{c}{b}_{j1}=-e_{j1}\sin \mathrm{\λ}+e_{j2}\cos \mathrm{\λ}\\ b_{j2}=-e_{j1}\sin L\cos \mathrm{\λ}-e_{j2}\sin L\sin \mathrm{\λ}+e_{j3}\cos L\\ b_{j3}=e_{j1}\cos L\cos \mathrm{\λ}+e_{j2}\cos L\sin \mathrm{\λ}+e_{j3}\sin L\end{array}\right\}$

$\left.\begin{array}{c}{a}_{j1}=(R_n+h)[-e_{j1}\sin L\cos \mathrm{\λ}-\sin L\sin \mathrm{\λ}]+[R_n{(1-e)}^2+h]e_{j3}\cos L\\ a_{j2}=(R_n+h)[e_{j2}\cos L\cos \mathrm{\λ}-\cos L\sin \mathrm{\λ}]\\ a_{j2}=e_{j1}\cos L\cos \mathrm{\λ}+e_{j2}\cos L\sin \mathrm{\λ}\end{array}\right\}---\left(14\right)$

Wherein, λ is the latitude of carrier, and L is the longitude of carrier.The state equation of hypercompact integrated kalman filter subsystem is identical with tight combination, the MINS that I, Q information and the step (2) that obtains according to GPS software receiver parsing in the step (1) obtains is to I, the Q information of gps satellite, can get the measurement equation of hypercompact integrated kalman filter subsystem, be designated as

Z _k＝H _kX _k+V _k (15)

Wherein

$H=\left[\right\{h_{\mathrm{xi}},h_{\mathrm{yi}},h_{\mathrm{zi}},\mathrm{0,0},...,\mathrm{1,0}\},\{h_{\stackrel{.}{x}i},h_{\stackrel{.}{y}i},h_{\stackrel{.}{z}i},\mathrm{0,0},...,\mathrm{0,1}\}{]}_{i=1:n}---\left(16\right)$

And

$\frac{\∂{\mathrm{\ω}}_e}{\∂x}=\frac{\mathrm{\ω}}{c}\frac{x_e}{R_e},$ $\frac{\∂{\mathrm{\ω}}_e}{\∂y}=\frac{\mathrm{\ω}}{c}\frac{y_e}{R_e},$ $\frac{\∂{\mathrm{\ω}}_e}{\∂z}=\frac{\mathrm{\ω}}{c}\frac{z_e}{R_e}$

$\frac{{\∂\mathrm{\ω}}_e}{\∂\stackrel{.}{x}}=\frac{\mathrm{\ω}}{c{R}_e},$ $\frac{\∂{\mathrm{\ω}}_e}{\∂\stackrel{.}{y}}=\frac{\mathrm{\ω}}{{\mathrm{cR}}_e},$ $\frac{{\∂\mathrm{\ω}}_e}{\∂\stackrel{.}{z}}=\frac{\mathrm{\ω}}{{\mathrm{cR}}_e}$

(4) utilize EKF that described GPS navigation data, MINS inertial navigation data are carried out data fusion in senior filter, generate navigation data

The state equation of senior filter is identical with subfilter, and the velocity location information that obtains according to step (1) and step (2) can get the system measurements equation, is designated as

$Z\left(t\right)=\left[\begin{array}{c}{Z}_P\left(t\right)\\ Z_V\left(t\right)\end{array}\right]=\left[\begin{array}{c}{H}_P\left(t\right)\\ H_V\left(t\right)\end{array}\right]X\left(t\right)+\left[\begin{array}{c}{V}_P\left(t\right)\\ V_V\left(t\right)\end{array}\right]=H\left(t\right)X\left(t\right)+V\left(t\right)---\left(17\right)$

Wherein

H _V(t)＝[0 _3×3?diag[1?1?1]0 _3×9]，H _P(t)＝[diag[1?1?1]0 _3×12] (18)

(5) the output navigation information comprises position, speed, attitude and the error thereof of carrier on three directions.

The present invention is according to gps signal intensity and carrier movement state, intelligent adaptive mates the integrated mode of primary/secondary navigational system, limited navigation data is fully merged, make total system have the advantage of GPS and MINS concurrently, it is wide finally to reach the navigation overlay area, dynamic response is good, the navigation accuracy advantages of higher.

As shown in Figure 2, the method step of present embodiment is as follows:

(1), and resolves generation GPS navigation data by GPS software receiver receiving satellite signal

The GPS software receiver that the present invention uses, front end is the NewStar210A of Beijing Orient couple stars company, the if sampling frequency is 16.367667MHz, digital intermediate frequency frequency 4.123968MHz.

Export real-time I, Q information by the tracking loop of GPS software receiver, and estimate the carrier doppler frequency displacement and calculate real-time pseudorange rates information.In the present embodiment, the output frequency of I, Q information is 1000Hz, and pseudorange, pseudorange rates data output frequency are 1Hz.Wherein I, Q obtain as follows:

Wherein,

With Be respectively the frequency and the phase place that receive gps signal, ω ' and

Be respectively local frequency and the phase place that produces, η is a noise.The moment with the arrival GPS software receiver of first satellite is a benchmark, obtain all visible satellites time of arrival poor of satellite therewith, can try to achieve the relative pseudorange of different satellites to receiver, the carrier doppler frequency displacement that estimates in real time according to the receiver tracking ring again can calculate real-time pseudorange rates information.

After obtaining navigation message, decode obtaining the ephemeris of gps satellite, and carry out bearer rate and location compute by ephemeris and corresponding pseudorange, pseudorange rates information.

(2) gather inertial navigation data by the inertial navigation unit, and resolve the generation inertial navigation data

Present embodiment uses the MEMS gyro, and the output frequency of gyro and accelerometer data is 100Hz, and the navigation error data output frequency is 1Hz.The initial position of carrier is 32.05856 ° of north latitude, 118.78864 ° of east longitudes, 93 meters of height; Three initial direction gyroscope constant value drifts are 0.5 °/h, and random drift is 0.1 °/h; Three initial directional acceleration meters often are worth biasing and are 0.3mg, are biased to 0.05mg at random.According to the bearer rate positional information that calculates, calculate corresponding I, Q information and pseudorange, pseudorange rates information.

(3) according to above-mentioned data select the navigation main system and with the array mode of backup system, constitute the Kalman filtering subsystem;

Present embodiment is the gps signal blind area under the non-high dynamic environment, selection MINS is a main system, carry out hypercompact combination with gps system, be about to I, Q information that I, Q information and MINS that the GPS software receiver obtains dope according to bearer rate, position and gps satellite ephemeris and in the Kalman filtering subsystem, carry out data fusion to proofread and correct MINS.The initial parameter of Kalman filtering subsystem is set as follows:

P ₀＝diag{0?0?0?(0.1m/s) ²?(0.1m/s) ²?(0.1m/s) ²?(0.5°) ²?(0.5°) ²?(0.5°) ²?(0.3mg) ²(0.3mg) ²?(0.3mg) ²?(0.5°/h) ²?(0.5°/h) ²?(0.5°/h) ²?1e-4?1e-8}，

Q ₀＝diag{0?0?0?(0.05mg) ²?(0.05mg) ²?(0.05mg) ²?(0.01°) ²?(0.01°) ²?(0.01°) ²?00?0?0?0?0?1e-4?1e-10}，

R ₀＝diag{varI ₁?varI ₂?varI ₃?varI ₄?varQ ₁?varQ ₂?varQ ₃?varQ ₄}。

(4) utilize federal Kalman filtering that described GPS navigation data, MINS inertial navigation data are carried out data fusion in senior filter, generate navigation data;

Adopt loose integrated mode, GPS software receiver and MINS are resolved the input as Kalman filter of the bearer rate that obtains, positional information, initial parameter is set as follows:

P ₀＝diag{0?0?0?(0.1m/s) ²?(0.1m/s) ²?(0.1m/s) ²?(0.5°) ²?(0.5°) ²?(0.5°) ²?(0.3mg) ²(0.3mg) ²?(0.3mg) ²?(0.5°/h) ²?(0.5°/h) ²?(0.5°/h) ²?(10m) ²?(0.1m/s) ²}，

Q ₀＝diag{0?0?0?(0.05mg) ²?(0.05mg) ²?(0.05mg) ²?(0.01°) ²?(0.01°) ²?(0.01°) ²?00?0?0?0?0?(5m) ²?(0.1m/s) ²，

R ₀＝diag{(10m) ²?(10m) ²?(10m) ²?(10m) ²?(0.2m/s) ²?(0.2m/s) ²?(0.2m/s) ²?(0.2m/s) ²}。

(5) output navigation information.

Comprise sky, carrier northeast three-dimensional velocity error, azimuth angle error, angle of pitch error, pitch angle error, longitude error, latitude error and height error.The result shows that velocity error is all less than 0.1m/s, and azimuth angle error is less than 0.04 ', and angle of pitch error is less than 0.68 ', and the pitch angle error is less than 0.83 ', and the three-dimensional site error is all less than 3.2m.Can effectively overcome the limitation of GPS positioning system in the applied environment of defective that MINS navigational system navigation error disperses in time and dynamically high or weak output signal based on the hypercompact combination navigation algorithm of GPS software receiver, navigation accuracy has not only surmounted the precision of single subsystem, and more extensive than the combination of simple pine, tight integrated mode adaptive surface, really realized vehicle-mounted seamless location.

Claims (5)

1. vehicle-mounted intelligent hypercompact combination navigation method based on the GPS software receiver is characterized in that may further comprise the steps:

(1), and, comprises gps signal carrier-to-noise ratio, visual star number amount, I, Q information, pseudorange pseudorange rates information and velocity location information with satellite-signal parsing generation GPS navigation data by GPS software receiver receiving satellite signal;

(2) gather inertial navigation data by the inertial navigation unit, and inertial navigation data is resolved formation speed positional information, I, Q information and pseudorange pseudorange rates information;

(3) according to above-mentioned data select the navigation main system and with the array mode of backup system, constitute the Kalman filtering subsystem;

(4) utilize EKF that described GPS navigation data, MINS inertial navigation data are carried out data fusion in senior filter, generate navigation data;

(5) the output navigation information is the described navigation data of step (4).

2. a kind of vehicle-mounted intelligent hypercompact combination navigation method based on the GPS software receiver according to claim 1 is characterized in that: in the described step (3), select the navigation main system and with the method for backup system array mode be:

(a) according to gps signal carrier-to-noise ratio, visual star number amount to judge the signal quality of GPS;

(b) according to the speed of carrier to judge whether being high dynamic environment;

When (c) non-high dynamic environment and gps signal were strong, selection MINS was a main system, carried out the pine combination with gps system, carried out data fusion to proofread and correct MINS in Kalman's senior filter, did not use the Kalman filtering subsystem;

When (d) non-high dynamic environment and gps signal were weak, selection MINS was a main system, tightly made up with gps system, and the pseudorange pseudorange rates information that is about to the two output is carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

(e) non-high dynamic environment and when being the gps signal blind area, selection MINS is a main system, carries out hypercompact combination with gps system, the I, the Q information that are about to the two output are carried out data fusion to proofread and correct MINS in the Kalman filtering subsystem;

(f) in the high dynamic environment, selection GPS is a main system, carries out hypercompact combination with MINS, and the I, the Q information that are about to the two output are carried out data fusion to proofread and correct GPS in the Kalman filtering subsystem.

3. a kind of vehicle-mounted intelligent hypercompact combination navigation method according to claim 1 based on the GPS software receiver, it is characterized in that: described step (4) generates final navigation data for the velocity location information of MINS and GPS output merges to proofread and correct main system in senior filter.

4. a kind of vehicle-mounted intelligent hypercompact combination navigation method according to claim 2 based on the GPS software receiver, it is characterized in that: judge that according to gps signal carrier-to-noise ratio, visual star number amount the gps signal method for quality is as follows in the described step (a): if carrier-to-noise ratio more than or equal to 35dB/Hz and visual star number amount more than or equal to 4, then gps signal is strong; If carrier-to-noise ratio more than or equal to 20dB/Hz and less than 35dB/Hz and visual star number amount more than or equal to 4, then gps signal is medium; If carrier-to-noise ratio less than 4, then is the gps signal blind area less than 20dB/Hz or number of satellites.

5. a kind of vehicle-mounted intelligent hypercompact combination navigation method according to claim 2 based on the GPS software receiver, it is characterized in that: in the described step (b) according to the speed of carrier judge whether into the method for high dynamic environment as follows: when bearer rate during more than or equal to 100m/s, be high dynamic environment, when bearer rate during, be non-high dynamic environment less than 100m/s.

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