CN1361433A - Complete integration positioning method for carrier - Google Patents

Abstract

The complete fusion method can be embodied by using not only available hardware but also future integral picture-level hardware. It includes the steps of: feeding signal from GPS antenna and predicted pseudo range and pseudo-range rate measurement from data fusing module, converting and tracking the signal to obtain pseudo range and pseudo-range rate measurement and their tracking error to data fusion module; receiving the angular rate and acceleration signal and data of the carrier from inertial measurement module, solving the navigation equation to obtain reference navigation parameters including position, speed and posture to the data fusion module; fusing the pseudo range and pseudo-range rate measurement and their tracking error, and reference navigation parameters to obtain the optimal estimation and positioning data of predicted pseudo range and pseudo-range rate measurement, reference navigation parameter error and inertial sensor error.

Description

The complete integration positioning method of carrier

The present invention relates to the localization method of operating body, more specifically say, be meant a kind of complete integration positioning method (Full Fusion Positioning Method) of carrier, wherein from the information of GPS, inertia angular rate sensor and inertial acceleration meter, by fusion treatment, so that obtain high performance locator data, satisfy the application scenario that some are had relatively high expectations to positioning performance, as long-term high precision, high anti-interference and high dynamic performance.

Only pipe is just in nearest decades, and the positioning system of carrier just extensively is familiar with by people, but it can be traced back to a long time ago.First carrier positioning system is two to take turns the guide battlebus in the world, and it is a kind of autostable range tie of 200-300 in Christian era (reportedly may more early) by China's invention.It is than the Zao millennium of magnetic compass appearance, and its principle of operation is based on a basic phenomenon, and when wheel changed direction, the distance that outer wheel is passed by was more than interior wheel, the simple mathematical function that this distance of walking is the course changing value more.When the course changes, gear by outer wheel drive, rotate a horizontal revolving stage, so that accurately offset the variation in course, so no matter how the course of guide battlebus changes, be installed in the arm of stretching out of the dummy on this horizontal revolving stage, always remain on the same direction pointer of similar compass.Along with the continuous progress of positioning system and other related-art technology, now existing different types of positioning system.

Along with the continuous progress of location systems art, low cost, little, the high-precision positioning system of volume will appear, and this system has the wide range of commercial using value.

The operating body positioning system will further be widened its range of application, as is used for car, taxi, motorbus, train, robot, mining, building, and the paging in personal mobile communication market and the data that resemble 911 urgent calls of cell-phone transmit.

To advanced person's commercial vehicle tracker, auto navigation and route guidance system, and intelligent vehicle freeway facility require to have the vehicle location ability, are the basic demands of these systems.

Worldwide, by technology such as application message, communication, location, controls, development intelligent expressway system.

In general, carrier localization method and system are voyage projectional technique system (DEADREELONING SYSTEM), radio positioning system, and commingled system (HYBRIDSYSTEM).The present invention is a kind of mixing, based on the operating body localization method of information fusion.

Calculate system based on the voyage that inertia angular speed and inertia angular accelerometer are measured, the position of carrier can be provided, and { information such as B attitude, it generally includes inertia measurement group (INERTIALMEASUREMENT UNIT) and processor.Inertial measurement cluster comprises that three quadratures are installed and the gyro of a plurality of crooked configurations, and three quadratures are installed and a plurality of crooked accelerometer, and other corresponding hardware.Gyro is used for measuring the angular speed of carrier, and accelerometer is used for measuring the acceleration of carrier.

These parts for stablizing a navigation coordinate are, and the angular motion of fusion vector, submit necessary information, in platform-type inertia system, this navigation coordinate system realizes that by framework in the strap down inertial navigation system, this navigation coordinate system is a parsing platform.

The navigation processing machine is handled carrier acceleration and the angular speed information of using from inertial measurement cluster.Given initial position and finishing after the initial alignment, system is data such as outgoing position, speed, attitude continuously.

Voyage based on inertia angular rate sensor and inertial acceleration sensor is calculated system, is commonly called inertial navigation positioning system or inertial reference system.It is compared with other positioning system, and biggest advantage is its autonomous operation characteristic completely and the frequency band with broad.

Yet the inertial positioning system cost is expensive and its error increases in time, and this mainly is owing to its sensor error, and as gyroscopic drift, accelerometer biasing and calibration factor error cause.

Usually, improving the method for the precision of inertial positioning system, is to adopt high-precision inertial sensor and adopt external sensor to assist inertial positioning system.

(Global Positioning System is satellite-based, global, round-the-clock radiolocation and time dissemination system GPS) to GPS, and it can be user endless, that receiving equipment is housed positioning service is provided.

The user must have receiver can obtain the service of GPS.A traditional single antenna GPS receiver, the code tracking loop by handling it and the pseudorange (Pseudo Range) of carrier tracking loop and pseudorange rates (Delta Range) are measured, three-dimensional position, speed and the temporal information of user's precision are provided, yet do not have attitude information.Under normal situation, the propagated error of gps signal and satellite error comprise and select availability (Selective Availability), have limited the error range of GPS.Yet gps signal is vulnerable to have a mind to or disturb and take advantage of volume unintentionally, and when attitude of carrier was motor-driven, gps antenna easily was blocked.In addition, lower or carrier is being done high dynamically when motor-driven when the gps signal noise ratio, and gps signal is easy to lose, thereby causes performance to reduce.

Along with the continuous minimizing of the cost and the volume of high-performance GPS receiver, many antenna GPS receiver adopts and interferes (Interferometric) phase techniques, and position and attitude information can be provided simultaneously.This technology is utilized the difference measurement of gps carrier phase place on the many antennas of GPS, obtains high-precision relative position measurement, is converted into attitude measurement then.The advantage of this technology is that attitude accuracy can keep long-term stability, and cost is lower, but the characteristic that still has narrow bandwidth and easily block or disturb, and the attitude of carrier that will obtain three is measured, must dispose 3 antennas at least, and require to separate as far as possible between the gps antenna, so that enough attitude resolution is arranged.

Because these latent defects of independent inertial positioning system and independent GPS receiver, need an independent inertial positioning system or an independent GPS, to satisfy the higher occasion of some performance requirements, as low-cost, long-term high precision, continuous output etc.

Because GPS receiver and inertial positioning system have complementary characteristic, therefore a lot of application scenarios, combined GPS/inertial positioning system can utilize two system's advantages separately, continuous navigation output can be provided, and have two inaccessiable high-performance of independent subsystem.Since the notion of GPS since proposing in 1973, existing much about the document of combined GPS/inertial positioning system aspect, and combined GPS/inertial positioning system has dropped into practical application.

The advantage of combined GPS/inertial positioning system can be summarized as follows:

1) can use inertial positioning data assistant GPS signal trace loop, thereby improve its tracking power under noise and dynamic environment.

2) after gps signal is temporarily lost, inertial positioning system not only can provide locator data, and can reduce and catch gps signal required search time again.

3) when gps signal can obtain, the error of the sum of errors inertial sensor of inertial positioning system can be corrected, and after gps signal was lost, inertial positioning system can keep high-precision output information in a period of time like this.

4) by means of carrier body, GPS can carry out moving alignment to inertial positioning system, thereby can cancel inertial positioning system required static-base alignment before entering normal running.

But above-mentioned feature performance benefit is not to be that the combined GPS/inertial positioning system of any level is all accessible.Now enumerate following several combined GPS/inertial positioning system:

1) position and the speed of use GPS, the readjustment inertial positioning system, this is the simplest a kind of array mode.

2) second method is called as tandem type (Cascaded Integration) combined GPS/inertial positioning system.In multiple array mode, the Kalman filter of combined GPS/inertial positioning system (Kalman Filter), use the output of the Kalman filter of GPS receiver inside, as its measurement, this method has the design feature of " the filtering road drives wave filter ".

3) the third method is called tight coupling (Tightly-Coupled) GPS/ inertial positioning system, in this combined method, the integrated kalman filter device is directly handled the original measurement value (pseudorange and pseudorange rates) of GPS receiver, obtains the optimal estimation of inertial positioning system error, inertial sensor error, GPS receiver clock error.The inertial positioning system data are used for the signal trace loop of assistant GPS receiver, in order to improve the signal trace performance of GPS receiver under noise and high dynamic environment.

Tight coupling GPS/ inertial positioning system is the result who strives for the potential advantage of combinations thereof GPS/ inertial positioning system.Although tight coupling GPS/ inertial positioning system has obtained practical application, but for the optimum combination that realizes the GPS/ inertial positioning system, traditional tight coupling GPS/ inertial positioning system still has many weak points, and this mainly is because the potential instability that the exchanges data deficiency is caused between two systems.

Bring the reason of latent instability to be for traditional tight coupling GPS/ inertial positioning system:

1) the auxiliary gps signal track loop of inertia has narrow bandwidth, and its time constant is greater than the update cycle of GPS/ inertia integrated kalman filter device, and the auxiliary error of inertia is filtered lentamente.The gps signal tracking error not only with time correlation, and relevant with the error of inertial positioning system of modeling in the integrated kalman filter device.Therefore, the statistical property that measured by the GPS pseudorange, pseudorange rates of the disturbance of gps signal tracking error, with integrated kalman filter be inconsistent to Testing requirement.

2) in traditional tight coupling GPS/ inertial positioning system, have a positive feedback loop: the inertial positioning data descend and can increase the tracking error of GPS receiver, and the precision that GPS measures can have a strong impact on the performance of the tuning integrated kalman filter device of low precision inertial positioning system, like this, error is measured by feed-in integrated kalman filter device at the GPS that increases and is handled, and can further cause the increase of the auxiliary error of inertia.

Except above-mentioned instability problem, traditional tight coupling GPS/ inertial positioning system and method are not easy to detect and isolate the signal of the gps satellite that breaks down, and this is because the integrated kalman filter device is handled all information in a concentrated manner.

Fundamental purpose of the present invention provides a kind of localization method of full fusion, wherein from the information of GPS, inertia angular rate sensor, inertial acceleration meter, handle to improve its performance in the mode of full fusion, satisfy the higher application scenario of some performance requirements, as long-term high precision, high dynamic capability, strong antijamming capability.The not only available existing hardware of the present invention is realized, and is more suitable for realizing with the hardware of the picture level integrated (Wafer ScaleIntegration) that occurs now.

Another object of the present invention is to provide a kind of localization method of full fusion, wherein adopted digital, multilayer signal/flow chart of data processing.

Another object of the present invention is to provide a kind of localization method of full fusion, and wherein traditional gps signal tracking based on phase-locked loop is realized that by a kind of the gps signal tracking replaces in total system.The tracking of gps signal is handled and is implemented in the whole GPS/ inertial positioning system, so that overcome the latent instability of traditional tight coupling GPS/ inertia system, strengthens the signal trace ability that GPS is dynamic at height and capable and experienced anti-environment closes.

Still a further object of the present invention is to provide a full localization method that merges, one of them maximum likelihood estimator module and fused filtering device provide the pseudorange of GPS and the tracking error of pseudorange rates, so that the correlation noise during the pseudorange of compensation GPS and pseudorange rates are measured, optimum navigational parameter after merging simultaneously is used for calculating pseudorange and the pseudorange rates of the GPS of prediction, the track loop of closed gps signal.

Still a further object of the present invention is to provide a full localization method that merges, and wherein the fused filtering device not only is used for merging the data of GPS and inertial sensor, and has the loop filtering function of gps signal track loop.

Still a further object of the present invention is to provide a full localization method that merges, and the fused filtering device that wherein has dual-use function uses the parallel Kalman filter of disperseing, and when breaking down with convenient gps satellite, wave filter can be reconstructed.

Still a further object of the present invention is to provide a full localization method that merges, and the Allowance Design that wherein adopts multilayer is to improve the reliability of system.

Still a further object of the present invention is to provide a full localization method that merges, and has wherein adopted the Allowance Design of multilayer, is convenient to realize the integrity monitoring of GPS.

For achieving the above object, method of the present invention may further comprise the steps:

1) feed-in is from the gps signal of gps antenna, and from the prediction pseudorange and the pseudorange rates conversion of data fusion with follow the tracks of gps signal, measures and tracking error to obtain pseudorange and pseudorange rates, with the above-mentioned data fusion module of its feed-in.

2) receive angular speed and acceleration signal, find the solution the inertial navigation equation, obtain the navigational parameter of reference, comprise position, speed, attitude, the above-mentioned data fusion module of its feed-in from the carrier of inertial measurement cluster.

3) merge above-mentioned pseudorange and pseudorange rates and measure and tracking error, and the navigation data of reference, the pseudorange and the pseudorange rates of acquisition prediction, with reference to the error of navigational parameter and inertial sensor, and optimum navigational parameter.

Fig. 1 is the complete integration positioning method block diagram of carrier,

Fig. 2 is the pre-service block diagram of gps signal,

Fig. 3 is the pretreated digital signal processing module block diagram of gps signal,

Fig. 4 is the Signal Pretreatment block diagram of inertial measurement cluster,

Fig. 5 is a kind of method of data fusion module,

Fig. 6 is the other method of data fusion module.

The present invention is the complete integration positioning method of gps signal and inertial sensor signal, so that the continuous position information of carrier is provided.To shown in Figure 6, complete integration positioning method of the present invention comprises the following step as Fig. 1:

1) feed-in is changed and pre-service it from the gps signal of gps antenna (5), so that obtain the measurement data of GPS, comprises pseudorange, pseudorange rates, and it is sent into data fusion module (80);

2) reception is found the solution the inertial navigation equation from the angular speed and the acceleration signal of the carrier of inertial measurement cluster (10), obtains the navigation data of reference, comprises position, speed etc., and it is sent into data fusion module (80);

3) merge the measurement data of above-mentioned GPS and with reference to the inertial navigation parameter, to obtain optimum locating information.

In order to improve system performance, in the 1st step, the tracking of gps signal is handled and is adopted open loop approach, and complete gps signal track loop is closed in data fusion module (80), to improve disturbing and the dynamic tolerance limit of carrier.

In order to improve the performance of system, in the 2nd step, be used for error in the compensate for reference navigation data from the optimal estimation of the reference navigation data errors of data fusion module (80).

As shown in Figure 2, the 1st step further comprises following steps:

(1-1) L section GPS RF (Radio Frequency) signal that receives by gps antenna (5), be admitted to a RF/IF (Intermediate Frequency) converter (21), the RF signal of input and carry out mixing from the local carrier signal of local digital controlled oscillator (24), signal after the mixing, be converted into intermediate-freuqncy signal through low-pass filtering, and export to an intermediate frequency base-band converter (22).

The GPS RF of gps satellite emission L1 wave band slightly catch (the L1 band signal of its i gps satellite emission is for Coarse Acquisition, C/A) sign indicating number and accurately sign indicating number (Precision Code, P sign indicating number) signal: $S_i^{L1}\left(t\right)=\sqrt{2P_c}\mathrm{CA}{\left(t\right)}_{i}D{\left(t\right)}_i\cos ({\mathrm{\ω}}_{1}t+\mathrm{\φ})+\sqrt{2P_p}P{\left(t\right)}_{i}D{\left(t\right)}_i\sin ({\mathrm{\ω}}_{1}t+\mathrm{\φ})$ Wherein: ω ₁It is the L1 carrier angular frequencies;

φ is little phase noise and oscillator drift part;

P _cBe the power of C/A coded signal;

P _pBe the power of P coded signal;

CA (t) is the C/A sign indicating number;

P (t) is the P sign indicating number;

D (t) is a navigation data.

Gps satellite is also launched the RF P coded signal of L2 wave band.The L2 signal of I gps satellite emission can be expressed as: $S_i^{L2}\left(t\right)=\sqrt{2P_2}P{\left(t\right)}_{i}D{\left(t\right)}_i\cos ({\mathrm{\ω}}_{2}t+{\mathrm{\φ}}_2),$ Wherein: ω ₂It is the L2 carrier angular frequencies;

P ₂Be the power of P2 P coded signal;

φ ₂Be little phase noise and oscillator drift part;

P (t) is the P sign indicating number;

D (t) is a navigation data.

These signals are with light velocity propagation, and the gps signal that is received by gps antenna (5) can be expressed as: L1: $S_i^{L1}\left(t\right)=\sqrt{2P_c}C{A}_i\left(t{-\mathrm{\τ}}_i\right)D_i\left(t\right)\cos [({\mathrm{\ω}}_1+{\mathrm{\ω}}_{\mathrm{id}})t+\mathrm{\φ})]+\sqrt{2P_p}{P}_i\left(t\right)D_i\left(t\right)\sin [({\mathrm{\ω}}_1+{\mathrm{\ω}}_{\mathrm{id}})t+\mathrm{\φ}\left)\right]$ L2： $S_i^{L2}\left(t\right)=\sqrt{2P_2}{P}_i(t-{\mathrm{\τ}}_i)D_i\left(t\right)\cos [({\mathrm{\ω}}_2+{\mathrm{\ω}}_{\mathrm{id}})t+{\mathrm{\φ}}_2)],$ Wherein: τ is the sign indicating number time-delay;

ω _dIt is the doppler angle frequency;

I represents i gps satellite.

The gps signal that gps antenna (5) receives is by the RF/IF converter (21) of feed-in GPS pre-service (20).

(1-2) received by IF/ baseband converter (22) from the GPS IF signal of RF/IF converter (21), the IF signal carries out mixing with signal from local digital controlled oscillator (24), and the signal after the mixing is exaggerated, low-pass filtering, is converted to baseband signal.The bandwidth of the C/A coded signal being carried out the low-pass filter of filtering is 1.023MHz, and the bandwidth of the P coded signal being carried out the wave filter of low-pass filtering is 10.23MHz.This baseband signal is admitted to A/D converter (23).

(1-3) baseband signal from the IF/ baseband converter is a simulating signal, and it is received by A/D converter (23), and the baseband signal of simulation is sampled, and forms digital signal.Its sample frequency is that (frequency of C/A coded signal is 2.1518MHz, and the frequency of P coded signal is 21.518MHz for 2 times of pseudo random signal frequency.)。The digital signal of output is by feed-in digital signal processor (25).The digital L1 CA signal of i satellite of A/D converter output can be expressed as: r _i(n)=A _iCA _i[(1+ ζ _i) nT _S-ζ _iT _P] cos[(ω _b+ ω _Id) n+ φ ₀]+N (n) is wherein: A: signal amplitude;

CA[... ]: bit rate is R, compares with gps time, delays time to be τ=ξ T _P± the PRN signal of 1 amplitude, its bit rate equals (1+ ζ) R ₀, here,

, F _LBe the GPSRF signal(-) carrier frequency, R ₀It is the bit rate of Doppler shift (Doppler Frequency);

Ts is the sampling period;

ω _bEqual 2 π f _bT _s, be base band angular frequency f _bDigital angular frequency;

ω _dEqual 2 π f _dT _s, be Doppler shift f _dDigital angular frequency;

φ ₀Original carrier phase place when being n=o;

N (n) is equivalent Gauss (Gaussian) noise of baseband frequency.

(1-4) shown in Fig. 2 and 3, drift about from the digital baseband signal of A/D transducer (23) with from the sign indicating number time-delay and the carrier doppler of the prediction of data fusion module (80), received by digital signal processor (25), be used for calculating pseudorange and pseudorange rates and measure, and the tracking error of pseudorange and pseudorange rates.

The local reference signal that is produced by digital controlled oscillator (24) is imported into RF/IF transducer (21), IF/ baseband converter (22) and digital signal processor (25).

As shown in Figure 3, from the digital signal of A/D converter (23) and local homophase (In-phase from sine-cosine generator (29), I) and quadrature (Quadraphase, Q) signal carries out mixing in frequency mixer (26), the signal after the mixing is admitted to correlator (27).From frequency mixer (26) through the quadrature of mixing and in-phase signal with from the local code of code generator (30), carry out relevant treatment in correlator (27), the result of relevant treatment is transfused to maximum likelihood estimator module (Maximum Likelihood Estimator) (28).

Come the correlation computations result of autocorrelator (27), gathered by maximum likelihood estimator module (28).Suppose in one hour time period, sign indicating number time-delay and carrier doppler are normal values, maximum likelihood estimator module can be made the maximal possibility estimation of the tracking error of sign indicating number time-delay and carrier doppler frequency displacement, and is converted into the tracking error of pseudorange and pseudorange rates, exports to data fusion module (80) again.

By feed-in sign indicating number oscillator (31), in order to calculate bit rate, certain bit rate PRN of generation (Pseudo-random Noise) sign indicating number is by feed-in code generator (30) from the Doppler shift of the prediction of data fusion module (80).

From the PRN sign indicating number of certain bit rate of code generator and from the sign indicating number time-delay of the prediction of data fusion module (80) by feed-in code generator (30), be used for producing local punctual code and compute pseudo-ranges, pseudorange rates is measured.The local punctual code that produces is admitted to correlator (27), and the demodulation of satellite almanac data, and the satellite ephemeris that demodulates is admitted to data fusion module (80), and pseudorange that draws and pseudorange rates measurement are admitted to data fusion module (80).

By feed-in sine-cosine generator (29), in order to producing local homophase and orthogonal signal, and the compute pseudo-ranges rate is measured from the carrier doppler frequency displacement of data fusion module (80).The homophase and the orthogonal signal that produce are admitted to frequency mixer (26), and the pseudorange rates measurement that draws is admitted to data fusion module (80).

As shown in Figure 4, the 2nd step has two kinds of operator schemes:

1) feedback compensation (Feedback Compensation);

2) feedforward compensation (Feedforward Compensation).

The angular speed of carrier and acceleration information can be provided by following two kinds of inertial measurement clusters:

1) comprises the inertial measurement cluster of the accelerometer that gyro that three quadratures install and three quadratures install, output tri-axis angular rate and acceleration information.

2) comprise the gyro of tilting installation more than three and the accelerometer of tilting installation more than three, the angular speed and the acceleration information of output remaining.

Thereby the 2nd step further comprises:

2 (A). the Signal Pretreatment of inertial measurement cluster (50) adopts the feedback compensation mode, this inertial measurement cluster comprises gyro and three accelerometers that quadrature is installed that three quadratures are installed, the tri-axis angular rate of its output and acceleration information and from the optimal estimation of the inertial sensor error of data fusion module (80) are transfused to the error compensation module (52) of the Signal Pretreatment part of inertial measurement cluster (50).

Compensate error in tri-axis angular rate and the acceleration with the optimal estimation of inertia sensor error, the tri-axis angular rate after error compensation is exported to attitude square computing module (53), and the acceleration after error compensation is exported to coordinate transformation module (54).

From the carrier angular rate data of error compensation module (52), from the rotating vector from local navigation coordinate system (n system) to inertial coordinates system (i system) of the earth and carrier angular speed computing module (26) and from the optimal estimation of the reference navigational parameter error of data fusion module (80), be imported into attitude matrix computing module (53), be used for upgrading the attitude matrix of body axis system, compensate the error of attitude matrix simultaneously to navigation coordinate system.The attitude matrix that draws is exported to coordinate transformation module (54) and with reference to navigation data computing module (56).The method of upgrading attitude matrix has Euler (Euler) method, direction cosine (Direction Cosine) method, hypercomplex number (quaternion) method.

Acceleration information from error compensation module (52), be expressed in the body axis system, it and from the attitude matrix of Attitude Calculation module (53), received by coordinate transferring (54), and the acceleration that will be expressed in the body axis system is converted to the acceleration that is expressed in the navigation coordinate system, and exports to reference to navigational parameter computing module (56).

From coordinate transformation module (54) be expressed in acceleration in the navigation coordinate system, from the attitude matrix of attitude matrix computing module (53) and from the optimal estimation of the reference navigational parameter error of data fusion module (80), received with reference to navigational parameter computing module (56), be used for calculating position, speed, the attitude data of reference, and the error of compensated position, speed, attitude data.The reference navigational parameter that draws comprises position, speed, attitude, exports to the data fusion module (80) and the earth and carrier angular speed computing module (55).

Come the reference navigational parameter of self-reference navigational parameter computing module (56), received by the earth and carrier angular speed computing module (55), be used for calculating the rotation angle speed that local navigation coordinate is tied to inertial coordinates system, and output it to attitude matrix computing module (53).

2 (b). the feedforward compensation mode is adopted in the pre-service of inertial measurement cluster (50), this inertial measurement cluster comprises gyro and three accelerometers that quadrature is installed that three quadratures are installed, and the tri-axis angular rate and the acceleration information of its output are carried out pre-service (50) by the feed-in inertial measurement cluster.The tri-axis angular rate data are by feed-in attitude matrix computing module (53), and 3-axis acceleration is by feed-in coordinate transformation module (54).

From the carrier angular rate data of inertial measurement cluster, from rotating vector of the earth and carrier angular speed computing module (26) from local navigation coordinate system (n system) to inertial coordinates system (i system), be imported into attitude matrix computing module (53), be used for upgrading the attitude matrix of body axis system, compensate the error of attitude matrix simultaneously to navigation coordinate system.The attitude matrix that draws is exported to coordinate transformation module (54) and with reference to navigation data computing module (56).The method of upgrading attitude matrix has Euler method, direction cosine method, hypercomplex number method.

Acceleration information from inertial measurement cluster, be expressed in the body axis system, it and from the attitude matrix of Attitude Calculation module (53), received by coordinate transferring (54), and the acceleration that will be expressed in the body axis system is converted to the acceleration that is expressed in the navigation coordinate system, and exports to reference to navigational parameter computing module (56).

From coordinate transformation module (54) be expressed in acceleration in the navigation coordinate system, from the attitude matrix of attitude matrix computing module (53), received with reference to navigational parameter computing module (56), be used for calculating position, speed, the attitude data of reference, the reference navigational parameter that draws comprises position, speed, attitude, exports to the data fusion module (80) and the earth and carrier angular speed computing module (55).

Come the reference navigational parameter of self-reference navigational parameter computing module (56), received by the earth and carrier angular speed computing module (55), be used for calculating the rotation angle speed that local navigation coordinate is tied to inertial coordinates system, and output it to attitude matrix computing module (53).

2 (c). the Signal Pretreatment of inertial measurement cluster (50) adopts the feedback compensation mode, this inertial measurement cluster comprises three with the gyro of tilting installation and the accelerometer of tilting installation more than three, the angular speed of the remaining of its output and acceleration information, by feed-in FDIR module, be used for carrying out the detection of sensor fault, isolate, reconstruct, export reliable tri-axis angular rate and acceleration information, the tri-axis angular rate and the acceleration information of output, and, be imported into the error compensation module (52) of the Signal Pretreatment part of inertial measurement cluster (50) from the optimal estimation of the inertial sensor error of data fusion module (80).

Compensate error in tri-axis angular rate and the acceleration with the optimal estimation of inertia sensor error, the angular speed after error compensation is exported to attitude square computing module (53), and the acceleration after error compensation is exported to coordinate transformation module (54).

From the carrier angular rate data of error compensation module (52), from the rotating vector from local navigation coordinate system (n system) to inertial coordinates system (i system) of the earth and carrier angular speed computing module (26) and from the optimal estimation of the reference navigational parameter error of data fusion module (80), be imported into attitude matrix computing module (53), be used for upgrading the attitude matrix of body axis system, compensate the error of attitude matrix simultaneously to navigation coordinate system.The attitude matrix that draws is exported to coordinate transformation module (54) and with reference to navigation data computing module (56).

The method of upgrading attitude matrix has Euler method, direction cosine method, hypercomplex number method.

Acceleration information from error compensation module (52), be expressed in the body axis system, it and from the attitude matrix of Attitude Calculation module (53), received by coordinate transferring (54), and the acceleration that will be expressed in the body axis system is converted to the acceleration that is expressed in the navigation coordinate system, and exports to reference to navigational parameter computing module (56).

From coordinate transformation module (54) be expressed in acceleration in the navigation coordinate system, from the attitude matrix of attitude matrix computing module (53) and from the optimal estimation of the reference navigational parameter error of data fusion module (80), received with reference to navigational parameter computing module (56), be used for calculating position, speed, the attitude data of reference, and the error of compensated position, speed, attitude data.The reference navigational parameter that draws comprises position, speed, attitude, exports to the data fusion module (80) and the earth and carrier angular speed computing module (55).

Come the reference navigational parameter of self-reference navigational parameter computing module (56), received by the earth and carrier angular speed computing module (55), be used for calculating the rotation angle speed that local navigation coordinate is tied to inertial coordinates system, and output it to attitude matrix computing module (53).

2 (d). feedforward compensation is adopted in the pre-service of inertial measurement cluster (50), this inertial measurement cluster comprises the gyro of tilting installation more than three and the accelerometer of tilting installation more than three, the angular speed of the remaining of its output and acceleration information, by feed-in FDIR module, be used for carrying out detection, isolation, the reconstruct of sensor fault, export reliable tri-axis angular rate and acceleration information.The tri-axis angular rate data are by feed-in attitude matrix computing module (53), and 3-axis acceleration is by feed-in coordinate transformation module (54).

From the carrier angular rate data of inertial measurement cluster, from rotating vector of the earth and carrier angular speed computing module (26) from local navigation coordinate system (n system) to inertial coordinates system (i system), be transfused to attitude matrix computing module (53), be used for upgrading the attitude matrix of body axis system, compensate the error of attitude matrix simultaneously to navigation coordinate system.The attitude matrix that draws is exported to coordinate transformation module (54) and with reference to navigation data computing module (56).

The method of upgrading attitude matrix has Euler method, direction cosine method, hypercomplex number method.

Acceleration information from inertial measurement cluster, be expressed in the body axis system, it and from the attitude matrix of Attitude Calculation module (53), received by coordinate transferring (54), and the acceleration that will be expressed in the body axis system is converted to the acceleration that is expressed in the navigation coordinate system, and exports to reference to navigational parameter computing module (56).

From coordinate transformation module (54) be expressed in acceleration in the navigation coordinate system, from the attitude matrix of attitude matrix computing module (53), received with reference to navigational parameter computing module (56), be used for calculating position, speed, the attitude data of reference, the reference navigational parameter that draws comprises position, speed, attitude, exports to the data fusion module (80) and the earth and carrier angular speed computing module (55).

Come the reference navigational parameter of self-reference navigational parameter computing module (56), received by the earth and carrier angular speed computing module (55), be used for calculating the rotation angle speed that local navigation coordinate is tied to inertial coordinates system, and output it to attitude matrix computing module (53).

As illustrated in Figures 5 and 6, the 3rd step can realize with following two schemes:

3 (a). based on Kalman filter (the Centralized Kalman Filter) scheme of centralized processing;

3 (b). based on distributing Kalman filtering (Decentralized Filter) scheme of disperseing parallel processing, such as associating (Federated) Kalman filtering.

As illustrated in Figures 5 and 6, the 3rd (a) step further comprises:

3 (a)-1. as illustrated in Figures 5 and 6, if the pre-service of inertial measurement cluster (50) realizes pre-service (50) closure of switch (90) and inertial measurement cluster then with the Error Feedback compensation way.Reference inertial navigation parameter from the pre-service (50) of inertial measurement cluster output, carried out error compensation by optimal estimation from the reference inertial navigation parameter error of centralized wave filter (81), and received by subtracter (82), pseudorange and the pseudorange rates computing module of being predicted by feed-in (83) is the locator data output as the full fusion of total system then.

If the pre-service of inertial measurement cluster (50) realizes with the error-feedforward compensation way, then switch (90) and subtracter (82) closure, from the reference navigational parameter of the pre-service (50) of inertial measurement cluster with from the optimal estimation of the reference navigational parameter error of concentrated filter (81), received by subtracter (82), and use the error of coming the compensate for reference navigational parameter with reference to the optimal estimation of navigational parameter error.Navigational parameter after the compensation is exported to the pseudorange and the pseudorange rates computing module (83) of prediction, and as the locator data output of the full fusion of total system.

From the satellite ephemeris of the digital signal processor (25) of the tracking passage of each gps satellite, from the reference navigation data of subtracter (90), from the receiver clock biasing of the GPS of concentrated filter (81) and the optimal estimation of clock drift, pseudorange and the pseudorange rates computing module (83) predicted by feed-in.

The pseudorange of the prediction of each passage and pseudorange rates can calculate with following parameters: the atmosphere time-delay of the signal of the receiver clock position of the position of the position of gps satellite and speed, inertial measurement cluster and speed, estimation and clock drift, deterministic gps satellite clock correction, calculating.

The pseudorange and the pseudorange rates of prediction are defeated by concentrated filter (81), and are converted into the sign indicating number time-delay and the carrier doppler frequency displacement of the gps signal of prediction, export to the digital signal processor (25) of each passage, in order to the tracking loop of closed gps signal.

3 (a)-2. comprise with reference to the navigational parameter error:

Three site errors, three velocity errors, three attitude errors and inertial sensor sum of errors GPS receiver error, modeling in concentrated filter (81), its differential equation can be expressed as: $\stackrel{\·}{X}\left(t\right)=F\left(t\right)X\left(t\right)+G\left(t\right)W\left(t\right)$

From the tracking error of the pseudorange of the measurement of the digital signal processor (25) of each passage and pseudorange rates, from the pseudorange of the prediction of prediction pseudorange and pseudorange rates computing module and the navigational parameter of pseudorange rates, satellite ephemeris and reference, received by concentrated filter (81) together, be used for carrying out following treatment step:

The parameter of update system and measurement equation;

The discrete model of computing system equation;

Calculate the linear model of measuring equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange of measurement and the pseudorange and the pseudorange rates of pseudorange rates and prediction are subtracted each other, and compensate, as the measurement of concentrated filter (81) with the tracking error of pseudorange and pseudorange rates;

Calculate and measure residual error;

Update mode is estimated and the variance battle array;

State estimation after the renewal is exported to subtracter (82) and inertial measurement cluster (50) carries out pre-service.

3 (a)-3. are transfused to FDIR (FailureDetection Isolation and Recovery) (84) from the measurement residual error of concentrated filter (81), be used for carrying out the statistical test of measuring residual error, isolate the input pseudorange that causes by the gps satellite fault and the fault of pseudorange rates so that detect.If the fault of detecting, the sign of fault satellites are exported to concentrated filter (81), so that isolated fault gps satellite or readjustment concentrated filter (81).

3 (b)-1. as shown in Figure 6, if the pre-service of inertial measurement cluster (50) realizes pre-service (50) closure of switch (90) and inertial measurement cluster then with the Error Feedback compensation way.Reference inertial navigation parameter from the pre-service (50) of inertial measurement cluster output, carried out error compensation by optimal estimation from the reference inertial navigation parameter error of centralized wave filter (81), and received by subtracter (82), pseudorange and the pseudorange rates computing module of being predicted by feed-in (83) then, and as the full locator data output of merging of total system.

If the pre-service of inertial measurement cluster (50) realizes with the error-feedforward compensation way, then switch (90) and subtracter (82) closure, from the reference navigational parameter of the pre-service (50) of inertial measurement cluster with from the optimal estimation of the reference navigational parameter error of concentrated filter (81), received by subtracter (82), and use the error of coming the compensate for reference navigational parameter with reference to the optimal estimation of navigational parameter error.Navigational parameter after the compensation is exported to the pseudorange and the pseudorange rates computing module (88) of prediction, and as the locator data output of the full fusion of total system.

From the satellite ephemeris of the digital signal processor (25) of the tracking passage of each gps satellite, from the reference navigation data of subtracter (90), from the receiver clock biasing of the GPS of concentrated filter (81) and the optimal estimation of clock drift, pseudorange and the pseudorange rates computing module (83) predicted by feed-in.

The pseudorange of the prediction of each passage and pseudorange rates can calculate with following parameters: the atmosphere time-delay of the signal of the receiver clock position of the position of the position of gps satellite and speed, inertial measurement cluster and speed, estimation and clock drift, deterministic gps satellite clock correction, calculating.

The pseudorange and the pseudorange rates of the prediction of the tracking passage of each gps satellite, be defeated by the local wave filter (85) of passage, and the sign indicating number that is converted into the gps signal of prediction is delayed time and the carrier doppler frequency displacement, export to the digital signal processor (25) of each passage, in order to the tracking loop of closed gps signal.

3 (b)-2. comprise with reference to the navigational parameter error: three site errors, three velocity errors, three attitude errors and inertial sensor sum of errors GPS receiver error, and modeling in each local wave filter (85), its differential equation can be expressed as: $\stackrel{\·}{X}\left(t\right)=F\left(t\right)X\left(t\right)+G\left(t\right)W\left(t\right)$

From the tracking error of the pseudorange of the measurement of the digital signal processor (25) of each passage and pseudorange rates, from the pseudorange of the prediction of the pseudorange of prediction and pseudorange rates computing module and the navigational parameter of pseudorange rates, satellite ephemeris and reference, received by corresponding each local wave filter (85) together, be used for carrying out following treatment step:

The parameter of update system and measurement equation;

The discrete model of computing system equation;

Calculate the linear model of measuring equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange of measurement and the pseudorange and the pseudorange rates of pseudorange rates and prediction are subtracted each other, and compensate, as the measurement of local wave filter (85) with the tracking error of pseudorange and pseudorange rates;

Calculate and measure residual error;

Update mode is estimated and the variance battle array;

State estimation after the renewal is exported to subtracter (82) and inertial measurement cluster (50) carries out pre-service.

3 (b)-3. estimate from the local state of each local wave filter and the variance battle array is exported to senior filter (86), are used for carrying out merging calculating, and draw the state estimation and the variance battle array thereof of global optimum, and output it to FDIR (89) and switch (91).

The state estimation of global optimum, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error, inertial sensor error, be fed back each local wave filter with the local wave filter of resetting, and the information that is used for carrying out between senior filter (86) and each the local wave filter is shared.

Communication between senior filter (86) and each local filter (85) and be used in senior filter (86) and local filter (85) in filtering method, can be with different modes, so that obtain different performance index.

3 (b)-4. estimate and the variance battle array from the local state of each local wave filter (85), estimate and the variance battle array with global state from senior filter (86), be used to carry out consistency check, measure so that can detect the out of order pseudorange and the pseudorange rates that cause by fault satellites and output signal.The sign of the detected fault of result, out of order gps satellite is exported to main filtering (86) by FDIR (89), so that reconstruct senior filter (86) is isolated out of order satellite.

Concerning GPS integrity (Integrity) monitoring, the performance of the FDIR of the 3rd (b) (89) is better than FDIR (89) performance of the 3rd (a) method.Because the 3rd (b) scheme has the parallel filtering structure.

Integrity is meant that system has the ability to provide instant alerting signal to stop its operation to the user.The problem that people are concerned about is that out of order gps satellite might send wrong navigation information to the user.When the alarm range of the navigation accuracy overshoot of GPS, require time of fire alarming within 10 seconds.But unfortunately the control section of GPS can not respond fault in this time restriction scope.Usually the GPS control section to spend time of 15 minutes to 1 hour determine GPS fault, pick out fault, determine correcting scheme, react.

Claims (42)

1. complete integration positioning method comprises the following step:

(a) gps signal received of feed-in one gps antenna and from the pseudorange and the pseudorange rates of data fusion module prediction, conversion, follow the tracks of this gps signal, obtain the pseudorange of GPS and the tracking error of pseudorange rates measurement and this pseudorange and pseudorange rates measurement, output it to described data fusion module;

(b) reception is found the solution the inertial navigation equation from the angular speed and the acceleration signal of the carrier of an inertial measurement cluster, obtains the navigational parameter of reference, comprises position, speed, attitude, and outputs it to described data fusion module;

(c) merge above-mentioned pseudorange and the tracking error of pseudorange rates measurement, pseudorange and pseudorange rates and the navigational parameter of above-mentioned reference, draw pseudorange, pseudorange rates, the optimal estimation of above-mentioned navigational parameter sum of errors inertial sensor error and the locator data of optimum of above-mentioned prediction.

2. complete integration positioning method as claimed in claim 1 is characterized in that, described (a) step further comprises:

(a-1) gps signal that receives from described gps antenna of output is given a RF/IF converter, and this gps signal is the RF signal, and with local GPS RF signal mixing from a local digital controlled oscillator; Signal after the mixing is carried out bandpass filtering, form intermediate-freuqncy signal, this intermediate-freuqncy signal is exported to a RF baseband converter;

(a-2) use local signal and this GPS IF signal from this this locality digital controlled oscillator to carry out mixing, the signal after the mixing is exaggerated, low-pass filtering, forms baseband signal, and this baseband signal is exported to an A/D converter;

(a-3) reception is from the baseband signal of described IF/ baseband converter, and this baseband signal is a simulating signal; By described A/D converter this baseband signal is sampled, form digital signal, and export to a digital signal processing module;

(a-4) from the digital signal of described A/D converter with from the sign indicating number time-delay and the carrier doppler frequency displacement of the prediction of data fusion module, received by described digital signal processing module, the pseudorange, the pseudorange rates that draw each tracking satellite are measured, and the tracking error measured of this pseudorange, pseudorange rates, and export to described data fusion module.

3. complete integration positioning method as claimed in claim 2 is characterized in that, described (a-4) step further comprises:

Receive above-mentioned digital signal from A/D converter, with its with carry out mixing from local homophase (I) and quadrature (Q) signal of one sine-cosine signal generator, quadrature after the output mixing and in-phase signal are to a correlation module;

Receive homophase after mixing and orthogonal signal and, carry out correlation computations, and the result of correlation computations is sent into a maximum likelihood estimator module by this correlation module from the local code of a code generator;

This maximum likelihood estimator module is collected N sampled value of described correlation module output, makes the maximal possibility estimation of the tracking error of sign indicating number time-delay and carrier doppler drift, and is converted into the tracking error of pseudorange, pseudorange rates, exports to described data fusion module;

By the carrier doppler frequency displacement of one yard oscillator reception, be used for calculating bit rate, and this sign indicating number is sent into a code generator from the prediction of described data fusion module;

By the sign indicating number of this code generator reception,, and output it to correlation module so that produce local punctual code from the given speed of this code generator; Compute pseudo-ranges is measured, and outputs it to described data fusion module; Carry out the demodulation of satellite ephemeris, and this satellite ephemeris is exported to described data fusion module;

By the carrier doppler frequency displacement of one sine-cosine signal generator reception from the prediction of data fusion module, produce above-mentioned I and Q signal, output it to above-mentioned frequency mixer; The compute pseudo-ranges rate is measured, and outputs it to data fusion module.

4. complete integration positioning method comprises following steps:

(a) gps signal received of feed-in one gps antenna and from the pseudorange and the pseudorange rates of data fusion module prediction, conversion, follow the tracks of this gps signal, obtain the pseudorange of GPS and the tracking error of pseudorange rates measurement and this pseudorange and pseudorange rates measurement, output it to described data fusion module;

(b) reception is from the angular speed and the acceleration signal of the carrier of an inertial measurement cluster, and from the optimal estimation of the reference navigational parameter sum of errors inertial sensor error of described data fusion module, find the solution navigation equation, draw this with reference to navigational parameter, comprise position, speed, attitude, and compensate this with reference to the error in the navigational parameter, the reference navigation data after over-compensation is sent into described data fusion module.

(c) merge above-mentioned pseudorange and the tracking error of pseudorange rates measurement, pseudorange and pseudorange rates and the navigational parameter of above-mentioned reference, draw pseudorange, pseudorange rates, the optimal estimation of above-mentioned navigational parameter sum of errors inertial sensor error and the locator data of optimum of above-mentioned prediction.

5. complete integration positioning method as claimed in claim 4 is characterized in that, described (a) step further comprises:

(a-1) gps signal that receives from described gps antenna of output is given a RF/IF converter, and this gps signal is the RF signal, and with local GPS RF signal mixing from a local digital controlled oscillator; Signal after the mixing is carried out bandpass filtering, form intermediate-freuqncy signal, this intermediate-freuqncy signal is exported to a RF baseband converter;

(a-2) use local signal and this GPS IF signal from this this locality digital controlled oscillator to carry out mixing, the signal after the mixing is exaggerated, low-pass filtering, forms baseband signal, and this baseband signal is exported to an A/D converter;

(a-3) reception is from the baseband signal of described IF/ baseband converter, and this baseband signal is a simulating signal; By described A/D converter this baseband signal is sampled, form digital signal, and export to a digital signal processing module;

(a-4) from the digital signal of described A/D converter with from the sign indicating number time-delay and the carrier doppler frequency displacement of the prediction of data fusion module, received by described digital signal processing module, the pseudorange, the pseudorange rates that draw each tracking satellite are measured, and the tracking error measured of this pseudorange, pseudorange rates, and export to described data fusion module.

6. complete integration positioning method as claimed in claim 5 is characterized in that, described (a-4) step further comprises:

Receive above-mentioned digital signal from A/D converter, with its with carry out mixing from local homophase (I) and quadrature (Q) signal of one sine-cosine signal generator, quadrature after the output mixing and in-phase signal are to a correlation module;

Receive homophase after mixing and orthogonal signal and, carry out correlation computations, and the result of correlation computations is sent into a maximum likelihood estimator module by this correlation module from the local code of a code generator;

This maximum likelihood estimator module is collected N sampled value of described correlation module output, makes the maximal possibility estimation of the tracking error of sign indicating number time-delay and carrier doppler drift, and is converted into the tracking error of pseudorange, pseudorange rates, exports to described data fusion module;

By the carrier doppler frequency displacement of one yard oscillator reception, be used for calculating bit rate, and this sign indicating number is sent into a code generator from the prediction of described data fusion module;

By the sign indicating number of this code generator reception,, and output it to correlation module so that produce local punctual code from the given speed of this code generator; Compute pseudo-ranges is measured, and outputs it to described data fusion module; Carry out the demodulation of satellite ephemeris, and this satellite ephemeris is exported to described data fusion module;

By the carrier doppler frequency displacement of one sine-cosine signal generator reception from the prediction of data fusion module, produce above-mentioned I and Q signal, output it to above-mentioned frequency mixer; The compute pseudo-ranges rate is measured, and outputs it to data fusion module.

7. complete integration positioning method as claimed in claim 4 is characterized in that, described (b) step comprises:

(b-1) input is from the tri-axis angular rate of described inertial measurement cluster and 3-axis acceleration and from the optimal estimation of the inertial sensor error of described data fusion, give an error compensation module, gyro and three accelerometers that quadrature is installed that this inertial measurement cluster has three quadratures to install;

(b-2) tri-axis angular rate and the 3-axis acceleration of importing with the optimal estimation compensation of this inertial sensor error, the tri-axis angular rate after the compensation is admitted to an attitude matrix computing module;

(b-3) by this attitude matrix computing module receive tri-axis angular rate from described error compensation module, from the earth and carrier angular speed computing module from local navigation coordinate be tied to the rotating vector of inertial coordinates system, from the optimal estimation of the reference navigational parameter error of described data fusion module, be used for upgrading the attitude matrix that to described navigation coordinate is from body axis system, and compensating error in this attitude matrix, this attitude matrix is admitted to above-mentioned coordinate transformation module and with reference to the navigational parameter computing module;

(b-4) by this coordinate transformation module receive from described error compensation module be expressed in the body axis system acceleration and from the attitude matrix of described attitude matrix computing module, the acceleration in the expression body axis system of input is converted to the acceleration calculation data that are expressed in navigation coordinate system;

(b-5) by above-mentioned with reference to the navigational parameter computing module, receive the acceleration that is expressed in navigation coordinate system of coordinate transformation module, from the attitude matrix of described attitude matrix computing module, from the optimal estimation of the reference navigational parameter error of described data fusion module, calculate above-mentioned reference position, speed, attitude, and compensate error in this position and the speed, with reference to navigational parameter, comprise that this reference position, speed, attitude export to the above-mentioned earth and carrier angular speed computing module and data fusion module with described;

(b-6) by this earth and carrier angular speed computing module, reception is from described reference navigational parameter with reference to the navigational parameter computing module, calculating above-mentioned is (n system) rotation angle speed with respect to inertial coordinates system from local navigation coordinate, and outputs it to above-mentioned attitude matrix computing module.

8. complete integration positioning method as claimed in claim 5 is characterized in that, described (b) step comprises:

(b-1) input is from the tri-axis angular rate of described inertial measurement cluster and 3-axis acceleration and from the optimal estimation of the inertial sensor error of described data fusion, give an error compensation module, gyro and three accelerometers that quadrature is installed that this inertial measurement cluster has three quadratures to install;

(b-2) tri-axis angular rate and the 3-axis acceleration of importing with the optimal estimation compensation of this inertial sensor error, the tri-axis angular rate after the compensation is admitted to an attitude matrix computing module;

(b-3) by this attitude matrix computing module receive tri-axis angular rate from described error compensation module, from the earth and carrier angular speed computing module from local navigation coordinate be tied to the rotating vector of inertial coordinates system, from the optimal estimation of the reference navigational parameter error of described data fusion module, be used for upgrading the attitude matrix that to described navigation coordinate is from body axis system, and compensating error in this attitude matrix, this attitude matrix is admitted to above-mentioned coordinate transformation module and with reference to the navigational parameter computing module;

(b-4) by this coordinate transformation module receive from described error compensation module be expressed in the body axis system acceleration and from the attitude matrix of described attitude matrix computing module, the acceleration in the expression body axis system of input is converted to the acceleration calculation data that are expressed in navigation coordinate system;

(b-5) by above-mentioned with reference to the navigational parameter computing module, receive the acceleration that is expressed in navigation coordinate system of coordinate transformation module, from the attitude matrix of described attitude matrix computing module, from the optimal estimation of the reference navigational parameter error of described data fusion module, calculate above-mentioned reference position, speed, attitude, and compensate error in this position and the speed, with reference to navigational parameter, comprise that this reference position, speed, attitude export to the above-mentioned earth and carrier angular speed computing module and data fusion module with described;

(b-6) by this earth and carrier angular speed computing module, reception is from described reference navigational parameter with reference to the navigational parameter computing module, calculating above-mentioned is (n system) rotation angle speed with respect to inertial coordinates system from local navigation coordinate, and outputs it to above-mentioned attitude matrix computing module.

9. complete integration positioning method as claimed in claim 6 is characterized in that, described (b) step comprises:

(b-1) input is from the tri-axis angular rate of described inertial measurement cluster and 3-axis acceleration and from the optimal estimation of the inertial sensor error of described data fusion, give an error compensation module, gyro and three accelerometers that quadrature is installed that this inertial measurement cluster has three quadratures to install;

(b-2) tri-axis angular rate and the 3-axis acceleration of importing with the optimal estimation compensation of this inertial sensor error, the tri-axis angular rate after the compensation is admitted to an attitude matrix computing module;

(b-3) by this attitude matrix computing module receive tri-axis angular rate from described error compensation module, from the earth and carrier angular speed computing module from local navigation coordinate be tied to the rotating vector of inertial coordinates system, from the optimal estimation of the reference navigational parameter error of described data fusion module, be used for upgrading the attitude matrix that to described navigation coordinate is from body axis system, and compensating error in this attitude matrix, this attitude matrix is admitted to above-mentioned coordinate transformation module and with reference to the navigational parameter computing module;

(b-4) by this coordinate transformation module receive from described error compensation module be expressed in the body axis system acceleration and from the attitude matrix of described attitude matrix computing module, the acceleration in the expression body axis system of input is converted to the acceleration calculation data that are expressed in navigation coordinate system;

(b-5) by above-mentioned with reference to the navigational parameter computing module, receive the acceleration that is expressed in navigation coordinate system of coordinate transformation module, from the attitude matrix of described attitude matrix computing module, from the optimal estimation of the reference navigational parameter error of described data fusion module, calculate above-mentioned reference position, speed, attitude, and compensate error in this position and the speed, with reference to navigational parameter, comprise that this reference position, speed, attitude export to the above-mentioned earth and carrier angular speed computing module and data fusion module with described;

(b-6) by this earth and carrier angular speed computing module, reception is from described reference navigational parameter with reference to the navigational parameter computing module, calculating above-mentioned is (n system) rotation angle speed with respect to inertial coordinates system from local navigation coordinate, and outputs it to above-mentioned attitude matrix computing module.

10. complete integration positioning method as claimed in claim 7 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned with reference to navigational parameter the position and the atmosphere time-delay of the gps signal of the clock biasing of the GPS receiver of speed, estimation and drift speed, definite gps satellite clock correction amount, calculating, calculate the pseudorange and the pseudorange rates of above-mentioned prediction;

(c-4) pseudorange and the pseudorange rates of exporting this prediction focuses on the formula wave filter to one, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that described each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by the described wave filter that focuses on to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) focus on by this that wave filter receives and handle from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the described measurement that focuses on wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error.

11. complete integration positioning method as claimed in claim 8 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned with reference to navigational parameter the position and the atmosphere time-delay of the gps signal of the clock biasing of the GPS receiver of speed, estimation and drift speed, definite gps satellite clock correction amount, calculating, calculate the pseudorange and the pseudorange rates of above-mentioned prediction;

(c-4) pseudorange and the pseudorange rates of exporting this prediction focuses on the formula wave filter to one, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that described each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by the described wave filter that focuses on to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) focus on by this that wave filter receives and handle from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the described measurement that focuses on wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error.

12. complete integration positioning method as claimed in claim 9 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned with reference to navigational parameter the position and the atmosphere time-delay of the gps signal of the clock biasing of the GPS receiver of speed, estimation and drift speed, definite gps satellite clock correction amount, calculating, calculate the pseudorange and the pseudorange rates of above-mentioned prediction;

(c-4) pseudorange and the pseudorange rates of exporting this prediction focuses on the formula wave filter to one, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that described each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by the described wave filter that focuses on to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) focus on by this that wave filter receives and handle from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the described measurement that focuses on wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error.

13. complete integration positioning method as claimed in claim 7 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

14. complete integration positioning method as claimed in claim 8 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

15. complete integration positioning method as claimed in claim 9 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

16. complete integration positioning method as claimed in claim 10 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

17. complete integration positioning method as claimed in claim 11 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

18. complete integration positioning method as claimed in claim 12 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

19. complete integration positioning method as claimed in claim 10 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

20. complete integration positioning method as claimed in claim 11 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

21. complete integration positioning method as claimed in claim 12 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

22. complete integration positioning method as claimed in claim 16 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

23. complete integration positioning method as claimed in claim 17 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

24. complete integration positioning method as claimed in claim 18 is characterized in that, further comprises an additional step after described (c-6) step:

(c-7) input is given a fault detect, isolation, reconstructed module (FDIR) from the measurement residual error of described centralized wave filter, in order to carry out the statistical test of this measurement residual error, to detect and to isolate because the input pseudorange and the pseudorange rates of the mistake that the gps satellite fault is caused, after detecting fault, fault satellites sign of FDIR module output is given center-filter, so that isolate this fault satellites or reset the described wave filter that focuses on.

25. complete integration positioning method as claimed in claim 7 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned position and the clock biasing of the GPS receiver of speed, estimation and drift speed, the really atmosphere time-delay of the gps signal of positive gps satellite clock correction amount, calculating with reference to navigational parameter, calculate pseudorange and pseudorange rates that above-mentioned each gps signal is followed the tracks of the prediction of passage;

(c-4) pseudorange and the pseudorange rates that is output as each gps signal tracking passage prediction follows the tracks of the set local wave filter of passage for corresponding above-mentioned each gps signal, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that above-mentioned each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by described local wave filter to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) receive and handle by above-mentioned local wave filter from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the measurement of described local wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned local optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error;

(c-7) receive by a senior filter and merge local optimum state estimation and covariance thereof, obtain the state estimation of global optimum from each local wave filter.

26. complete integration positioning method as claimed in claim 8 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned position and the clock biasing of the GPS receiver of speed, estimation and drift speed, the really atmosphere time-delay of the gps signal of positive gps satellite clock correction amount, calculating with reference to navigational parameter, calculate pseudorange and pseudorange rates that above-mentioned each gps signal is followed the tracks of the prediction of passage;

(c-4) pseudorange and the pseudorange rates that is output as each gps signal tracking passage prediction follows the tracks of the set local wave filter of passage for corresponding above-mentioned each gps signal, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that above-mentioned each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by described local wave filter to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) receive and handle by above-mentioned local wave filter from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the measurement of described local wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned local optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error;

(c-7) receive by a senior filter and merge local optimum state estimation and covariance thereof, obtain the state estimation of global optimum from each local wave filter.

27. complete integration positioning method as claimed in claim 9 is characterized in that, described (c) step comprises:

(c-1) export to the pseudorange and the pseudorange rates computing module of prediction with described with reference to navigational parameter, and as full locator data output of merging;

(c-2), receive from each gps signal and follow the tracks of the satellite ephemeris of the digital signal processing module of passage, above-mentioned optimal estimation with reference to navigational parameter and biasing of GPS receiver clock and drift by prediction pseudorange and pseudorange rates computing module;

(c-3) use the position of gps satellite and speed, above-mentioned position and the clock biasing of the GPS receiver of speed, estimation and drift speed, the really atmosphere time-delay of the gps signal of positive gps satellite clock correction amount, calculating with reference to navigational parameter, calculate pseudorange and pseudorange rates that above-mentioned each gps signal is followed the tracks of the prediction of passage;

(c-4) pseudorange and the pseudorange rates that is output as each gps signal tracking passage prediction follows the tracks of the set local wave filter of passage for corresponding above-mentioned each gps signal, and sign indicating number time-delay and carrier doppler that the pseudorange that will predict and pseudorange rates convert above-mentioned prediction to drift about, and output it to the digital signal processing module that above-mentioned each gps signal is followed the tracks of passage, be used for closed this gps signal tracking loop;

(c-5) by described local wave filter to reference navigational parameter error, comprise three site errors, three velocity errors, three attitude errors, the modeling of inertial sensor sum of errors GPS receiver error;

(c-6) receive and handle by above-mentioned local wave filter from above-mentioned each gps signal follow the tracks of passage digital signal processing module pseudorange and pseudorange rates is measured and the tracking error of this pseudorange and pseudorange rates, from the pseudorange of the prediction of the pseudorange of above-mentioned prediction and pseudorange rates computing module and the inertial navigation parameter of pseudorange rates and satellite ephemeris and reference, further comprise the following steps:

Update system and measurement equation;

Calculate the parameter of the discrete model of this system equation;

Calculate the parameter of the linear model of this measurement equation;

Computing mode is estimated and the time of variance battle array propagates;

The pseudorange and the pseudorange rates of above-mentioned measurement are compared with the pseudorange and the pseudorange rates of prediction, and compensate with the pseudorange of above-mentioned measurement and the tracking error of pseudorange rates, its result is as the measurement of described local wave filter;

Calculate and measure residual error, upgrade above-mentioned state estimation and variance battle array thereof, obtain above-mentioned local optimal estimation with reference to navigational parameter error, inertial sensor error, GPS receiver error;

(c-7) receive by a senior filter and merge local optimum state estimation and covariance thereof, obtain the state estimation of global optimum from each local wave filter.

28. complete integration positioning method as claimed in claim 25 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

29. complete integration positioning method as claimed in claim 26 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

30. complete integration positioning method as claimed in claim 27 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

31. complete integration positioning method as claimed in claim 28 is characterized in that, after described (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

32. complete integration positioning method as claimed in claim 29 is characterized in that, after described (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

33. complete integration positioning method as claimed in claim 30 is characterized in that, after described (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

34. complete integration positioning method as claimed in claim 25 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

35. complete integration positioning method as claimed in claim 26 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

36. complete integration positioning method as claimed in claim 27 is characterized in that, described (b-1) step may further comprise the steps:

(b-1-1) receive remaining angular speed and acceleration signal from an inertial measurement cluster, this inertial measurement cluster comprises the gyro and the accelerometer of the tilting configuration more than three;

(b-1-2) carry out fault detect and isolation;

(b-1-3) from the angular speed and acceleration information of remaining, solve tri-axis angular rate and acceleration information;

(b-1-4) with tri-axis angular rate and acceleration information and from the optimal estimation of the sensor error of described data fusion module, send into an error compensation module.

37. complete integration positioning method as claimed in claim 34 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

38. complete integration positioning method as claimed in claim 37 is characterized in that, after (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

39. complete integration positioning method as claimed in claim 35 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

40. complete integration positioning method as claimed in claim 39 is characterized in that, after described (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

41. complete integration positioning method as claimed in claim 36 is characterized in that, after described (c-7) step, further comprises additional step:

(c-8) reception is estimated and the variance battle array from the local state of described each local wave filter, and estimate and the variance battle array from the global optimum of senior filter, in order to carry out consistency check, so that be used for detecting and isolating the input pseudorange and the pseudorange rates of the mistake that is caused by the gps satellite fault, after detecting fault, fault satellites sign of FDIR module output is given senior filter, so that isolate this fault satellites or this senior filter of resetting.

42. complete integration positioning method as claimed in claim 41 is characterized in that, after described (c-7) step, further comprises an additional step:

Will be from the state estimation of the global optimum of described senior filter, the optimal estimation and the variance battle array thereof that comprise inertial navigation parameter error, GPS receiver error and inertial sensor error feed back to described each local wave filter, this this locality wave filter so that reset, the information of carrying out between this senior filter and each the local wave filter is shared.

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