CN114485650B - MEMS-INS assisted GNSS vector loop tracking method, device, storage medium and equipment - Google Patents
MEMS-INS assisted GNSS vector loop tracking method, device, storage medium and equipment Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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Abstract
The invention provides a MEMS-INS assisted GNSS vector loop tracking method, a device, a storage medium and equipment, wherein the method comprises the following steps: mixing the digital intermediate frequency signal with a signal generated by a carrier oscillator to obtain a receiving code, correlating with a local replica code generated by a code generator, integrating and removing to obtain six coherent integration results; the pseudo-range error and the pseudo-range rate error are acquired and sent to a navigation filter to calculate the rough position and speed information of the satellite navigation receiver at the current moment; under the condition that the carrier-to-noise ratio does not meet the preset condition, carrying out combined navigation of the miniature inertial navigation system and the global navigation satellite system by utilizing a volume Kalman filtering algorithm, and obtaining accurate position and speed information of the current moment by combining the rough position and speed information of the current moment; the pseudo range and the code frequency at the current moment are calculated and fed back to the code oscillator so that the code generator can generate a local copy code, the performance of a tracking loop can be improved, and the positioning accuracy and the positioning stability of the integrated navigation system can be improved.
Description
Technical Field
The present invention relates to the field of satellite positioning technologies, and in particular, to a method, an apparatus, a storage medium, and a device for MEMS-INS assisted GNSS vector loop tracking.
Background
With the increasing alternation of science and technology, the requirements of people on the tracking stability of motion carriers (ships, vehicles and planes) are higher and higher, and the acquisition of reliable position information becomes crucial. In recent years, the integrated navigation can fully utilize the advantages of each system, and is widely regarded as an effective alternative for independent GNSS navigation in a weak signal environment. The integrated navigation system has the advantages that the integrated navigation system assists in capturing and tracking satellite signals through the integrated navigation output result, the stability of the navigation system is improved, and the integrated navigation system can estimate and correct errors of the INS, so that the dispersion of the errors of the INS is restrained. Inertial devices such as laser gyroscopes, fiber optic gyroscopes, and the like are highly accurate, but expensive, MEMS-level accelerometers and gyroscopes are being widely used as low cost Inertial Measurement Unit (IMU) sensors, which, however, sacrifice the accuracy of integrated navigation systems.
Therefore, it is necessary to explore more advanced filtering fusion technology to improve the accuracy of the GNSS/MEMS-INS integrated navigation system.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a MEMS-INS assisted GNSS vector loop tracking method, a device, a storage medium and equipment, which aim to feed back an assisted code tracking loop by utilizing a combined navigation result obtained by CKF, improve the performance of the tracking loop, and improve the positioning precision and the positioning stability.
In a first aspect, an embodiment of the present invention provides a MEMS-INS assisted GNSS vector loop tracking method, including:
acquiring a digital intermediate frequency signal after the satellite signal frequency-reducing quantization;
mixing the digital intermediate frequency signal with a signal generated by a carrier oscillator to obtain a receiving code, correlating the receiving code with a local replica code generated by a code generator, and obtaining six coherent integration results after integration and removal;
acquiring a pseudo-range error and a pseudo-range rate error, and sending the pseudo-range error and the pseudo-range rate error into a navigation filter of a global navigation satellite system to calculate the rough position and speed information of the current moment of a satellite navigation receiver;
judging whether the carrier-to-noise ratio meets a preset condition or not;
under the condition that the carrier-to-noise ratio does not meet the preset condition, carrying out combined navigation of the miniature inertial navigation system and the global navigation satellite system by utilizing a volume Kalman filtering algorithm, and obtaining the accurate position and speed information of the satellite navigation receiver at the current moment by combining the rough position and speed information of the current moment;
calculating a pseudo range of the current moment;
and calculating the code frequency at the current moment, and feeding back to a code oscillator so as to enable the code generator to generate a local replica code, thereby realizing vector loop tracking.
In some embodiments, the mixing the digital intermediate frequency signal with a signal generated by a carrier oscillator to obtain a receiving code includes:
and the in-phase carrier signal and the opposite-phase carrier signal generated by the carrier oscillator are respectively mixed with the digital intermediate frequency signal to obtain a receiving code, wherein the opposite-phase carrier signal is subjected to 90-degree opposite phase and then mixed with the digital intermediate frequency signal.
In some embodiments, the acquiring the pseudorange error and the pseudorange rate error comprises:
the code ring discriminator discriminates the code phase difference between the k moment receiving code and the local copy code, and the code phase difference is linearly converted to obtain a pseudo-range error;
and predicting the carrier frequency at the moment k+1 by using a carrier ring discriminator, and obtaining a pseudo-range rate error by linear change of the carrier frequency at the moment k+1 and the carrier frequency difference value at the moment k.
In some embodiments, the performing integrated navigation of the micro inertial navigation system and the global navigation satellite system by using the volumetric kalman filtering algorithm, and obtaining accurate position and speed information of the satellite navigation receiver at the current moment by combining the rough position and speed information at the current moment includes:
setting a volume point through a spherical radial criterion, defining a combined navigation state quantity, wherein the combined navigation state quantity comprises an attitude error, a speed error, a position error, a gyro zero offset constant drift, an accelerometer random constant drift, a lever arm position error of MEMS-INS and GNSS and a time asynchronous error, and a CKF filter state initial value is set as a zero matrix;
calculating the mean value and the variance of the one-step prediction state value;
decomposing the variance of the one-step prediction state value, and updating the volume point again;
calculating the average value of the one-step prediction measurement value;
predicting the variance of the measurement values, and predicting the covariance of the state values and the one-step predicted measurement values;
calculating the volume Kalman gain, the posterior mean value of the target state and the posterior variance;
the posterior mean value of the target state is calculated based on the rough position and the speed information at the current moment.
In some embodiments, after the calculating the code frequency at the current time, feeding back the code frequency to the code oscillator to enable the code generator to generate the local replica code, returning the digital intermediate frequency signal to mix with the signal generated by the carrier oscillator to obtain the receiving code, and performing correlation between the receiving code and the local replica code generated by the code generator, and performing integration and removal to obtain six coherent integration results.
In some embodiments, the method further comprises:
and under the condition that the carrier-to-noise ratio meets the preset condition, directly executing the pseudo range of the current moment and the code frequency of the current moment, and feeding back the pseudo range and the code frequency to a code oscillator so as to enable the code generator to generate a local replica code, thereby realizing the step of vector loop tracking.
In some embodiments, under the condition that the carrier-to-noise ratio meets a preset condition, calculating a pseudo range of the current moment by combining the rough position and the speed information of the current moment of the satellite navigation receiver;
and under the condition that the carrier-to-noise ratio does not meet the preset condition, calculating the pseudo range of the current moment by combining the accurate position and speed information of the current moment of the satellite navigation receiver.
In a second aspect, an embodiment of the present invention provides a MEMS-INS assisted GNSS vector loop tracking apparatus, comprising:
the signal acquisition module is used for acquiring digital intermediate frequency signals after the satellite signals are subjected to frequency reduction quantization;
the code correlation module is used for mixing the digital intermediate frequency signal with the signal generated by the carrier oscillator to obtain a receiving code, correlating the receiving code with a local copy code generated by the code generator, and obtaining six coherent integration results after integration and removal;
the first calculation module is used for acquiring pseudo-range errors and pseudo-range rate errors, and sending the pseudo-range errors and the pseudo-range rate errors into a navigation filter of a global navigation satellite system to calculate the current time rough position and speed information of the satellite navigation receiver;
the judging module is used for judging whether the carrier-to-noise ratio meets the preset condition;
the CKF module is used for carrying out combined navigation of the miniature inertial navigation system and the global navigation satellite system by utilizing a volume Kalman filtering algorithm under the condition that the carrier-to-noise ratio does not meet the preset condition, and obtaining the accurate position and speed information of the satellite navigation receiver at the current moment by combining the rough position and speed information of the current moment;
the second calculation module is used for calculating the pseudo range of the current moment;
and the feedback module is used for calculating the code frequency at the current moment and feeding back the code frequency to the code oscillator so as to enable the code generator to generate a local copy code and realize vector loop tracking.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, where the computer program is executed by one or more processors to implement the MEMS-INS assisted GNSS vector loop tracking method according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including a memory and one or more processors, where the memory stores a computer program, and the computer program is executed by the one or more processors to implement the MEMS-INS assisted GNSS vector loop tracking method according to the first aspect.
Compared with the prior art, the combined navigation method combining the FLS and the UKF at least has the following beneficial effects:
on the basis of completing INS assisted GNSS loop tracking by using a vector tracking technology to realize integrated navigation, the CKF-based vector loop tracking method provided by the invention can improve the performance of a tracking loop, improve the positioning precision of an integrated navigation system and improve the positioning stability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be considered as limiting the scope.
FIG. 1 is a flow chart of a MEMS-INS assisted GNSS vector loop tracking method provided by the invention;
FIG. 2 is a schematic diagram of a MEMS-INS assisted GNSS vector loop tracking method provided by the invention;
FIG. 3 is a schematic diagram of a flow chart of the implementation of the volume Kalman filtering provided by the invention;
FIG. 4 is a graph comparing the positioning results of the MEMS-INS assisted GNSS vector loop tracking method provided by the invention;
FIG. 5 is a block diagram of a MEMS-INS assisted GNSS vector loop tracking device provided by the invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention.
It should be noted that, the illustrations provided in the present embodiment merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.
Example 1
Fig. 1 shows a flow chart of a MEMS-INS assisted GNSS vector loop tracking method, fig. 2 shows a schematic diagram of the method, and the MEMS-INS assisted GNSS vector loop tracking method shown in fig. 1 to 2 includes:
step S101, obtaining a digital intermediate frequency signal S after satellite signal down-conversion quantization IF 。
Step S102, digital intermediate frequency signal S IF Mixing with the signal generated by the local carrier oscillator to obtain receiving code, correlating the receiving code with local replica code (leading code E, instant code P and lagging code L) generated by the local code generator, integrating, removing (I&D) Six coherent integration results are obtained, wherein the result comprises a lead code E, an instant code P and a lag code L of the same-direction carrier signal I E 、I P 、I L Reverse carrier signal Q E 、Q P 、Q L 。
In some embodiments, the digital intermediate frequency signal S IF Mixing with a signal generated by a carrier oscillator to obtain a receiving code, comprising:
in-phase carrier signal generated by carrier oscillatorPhase carrier signals are respectively connected with digital intermediate frequency signals S IF Mixing to obtain a receiving code, wherein the inverted carrier signal is subjected to 90-degree inversion and then mixed with the digital intermediate frequency signal.
Step S103, acquiring pseudo-range errors and pseudo-range rate errors, and sending the pseudo-range errors and the pseudo-range rate errors into a navigation filter of a global navigation satellite system to calculate the current time rough position and speed information of the satellite navigation receiver.
In some embodiments, obtaining the pseudo-range error and the pseudo-range rate error in step S103 includes:
the code loop discriminator discriminates the code phase difference Deltaτ between the k-time received code and the locally replicated code k The code phase difference is subjected to linear conversion to obtain a pseudo-range error delta rho;
wherein f code The code frequency of the satellite signal is 1.023×10 in this embodiment -6 C is the speed of light.
Predicting the carrier frequency at time k+1 using a carrier loop discriminator (including a phase locked loop PLL), the carrier frequency f at time k+1 k+1 Carrier frequency f at time k k Is a difference Δf of (a) d Obtaining pseudo-range rate error through linear change
It will be appreciated that phase discrimination using a phase locked loop PLL, i.e. predicting the carrier frequency at time k +1, feeds back to the carrier oscillator to generate the signal at the next time.
Further, the pseudo-range difference Deltaρ and the pseudo-range rate error are calculatedSending the current rough position and speed information into a GNSS navigation filter to calculate the current rough position and speed information of the satellite navigation receiver.
Step S104, judging whether the carrier-to-noise ratio meets the preset condition.
In some cases, the preset condition is a carrier to noise ratio greater than 28.
Step 105, under the condition that the carrier-to-noise ratio does not meet the preset condition, performing integrated navigation of the micro inertial navigation system and the global navigation satellite system by utilizing a volume Kalman filtering algorithm, and obtaining the accurate position and speed information of the satellite navigation receiver at the current moment by combining the rough position and speed information of the current moment.
In some embodiments, in step S105, the combined navigation of the micro inertial navigation system and the global navigation satellite system is performed by using a volumetric kalman filtering algorithm, and the accurate position and speed information of the current moment of the satellite navigation receiver is obtained by combining the rough position and speed information of the current moment, including:
step S105a, setting the volume point by spherical radial criterionDefining the combined navigation state quantity as 19 dimensions, wherein the combined navigation state quantity comprises attitude errors phi in three directions, speed errors delta v in three directions, position errors delta p in three directions and zero offset drift epsilon of a gyro in three directions b Accelerometer random constant drift in three directions +.>Three-way MEMS-INS (including gyroscope and accelerometer) and GNSS lever arm position error δl b The initial value of the state of the CKF filter is set as zero matrix.
The calculation formula for the volume point acquisition is as follows:
wherein, xi i Is the set of volume points, n is the dimension of the state matrix; [1]Representing an identity matrix; p (P) k Is a covariance matrix;is an initial state quantity.
Step S105b, calculating the mean value of the one-step prediction state valuesVariance P k+1/k 。
Wherein phi is k+1/k Is a state transition matrix;
M aa ,M av ,M ap ,M va ,M vv ,M vp ,M pv ,M pp is the error propagation coefficient of INS;representing a navigational to carrier-based attitude matrix; 0 represents a zero matrix.
Variance P of one-step prediction state value k+1/k ：
In the above formula, Q is the variance of the system state noise, which includes noiseAnd->White noise of gyro angular velocity measurement, +.>Is the accelerometer specific force measurement white noise.
Step 105c, decomposing the variance of the one-step prediction state value, and updating the volume point again.
Step S105d, calculating the mean value of the one-step prediction measurement values
Wherein H is k+1 Is a measurement transfer matrix;
wherein, the liquid crystal display device comprises a liquid crystal display device,representing the angular velocity from the earth coordinate system to the carrier coordinate system,a n average linear acceleration of the carrier near the unsynchronized time, 1 representing a unit array; the superscript/subscript b denotes the carrier coordinate system and the superscript n denotes the navigation coordinate system.
Step S105e, predicting variance of the measurement valueAnd covariance of state value and one-step predictive measurement value +.>
In the above formula, R is the system measurement noise variance. The system measurement noise includes noise V v And V p ,V v White noise of satellite receiver speed measurement, V p White noise is measured at the satellite receiver location.
Step S105f, calculating the volume Kalman gain K k+1 Posterior mean of target statesPost-inspection variance P k+1 . The posterior mean value of the target state is calculated based on the rough position and the speed information at the current moment.
Wherein y is k+1 Is a measurement of the quantity of the sample,wherein->The speed and position results of INS and GNSS are represented, the speed and position results of INS can be directly obtained, and the speed and position results of GNSS are the rough position and speed information of the current time of the satellite navigation receiver obtained in step S103.
The implementation flow of the volume kalman filter is shown in fig. 3.
Step S106, calculating the pseudo range of the current moment.
Under the condition that the carrier-to-noise ratio meets the preset condition, the pseudo range of the current moment is calculated by directly combining the rough position and the speed information of the current moment of the satellite navigation receiver obtained in the step S103.
Under the condition that the carrier-to-noise ratio does not meet the preset condition, calculating the pseudo range of the current moment by combining the accurate position and speed information of the current moment of the satellite navigation receiver.
Combining CKF predicted receiver position P r,k Calculating pseudo range rho of current moment k Combining the CKF predicted state quantity and the position and speed of the GNSS filter obtained in step S105, more accurate receiver position and speed information can be obtained.
ρ k ＝||p r,k -p s ||+c(Δb-Δb s )+cI+cT+ε ρ (19)
Wherein P is r,k For the receiver position, Δb is the receiver clock bias, Δb s The clock difference of the satellite clock is that I is ionosphere delay, T is troposphere delay, epsilon ρ Is a pseudo-range measurement noise measurement.
Step S107, calculating the code frequency f at the current time code,k Feedback to the code oscillator to cause the code generator to generate a locally replicated code, realNow vector loop tracking.
Where Δt represents the update period.
According to the code frequency predicted by the combined navigation result (CKF predicted result), the code oscillator (code NCO) is adjusted to become a step signal, and the step signal is transmitted through the code generator to generate an advanced code E, an instant code P and a lagging code L, so that the code loop tracking is realized.
It should be understood that, in the case that the carrier-to-noise ratio satisfies the preset condition, the step S106 is directly executed to calculate the pseudo range of the current moment and the step S107 is executed to calculate the code frequency of the current moment, and the calculated code frequency is fed back to the code oscillator, so that the code generator generates the local replica code, thereby realizing the vector loop tracking.
After calculating the code frequency at the current moment, feeding back to the code oscillator to enable the code generator to generate the local replica code, returning to the step S102 of mixing the digital intermediate frequency signal with the signal generated by the carrier oscillator to obtain the receiving code, correlating the receiving code with the local replica code generated by the code generator, integrating and clearing to obtain six coherent integration results.
Fig. 4 shows a comparison of positioning results of the MEMS-INS assisted GNSS vector loop tracking method in an embodiment, and it can be seen that the combined navigation result obtained by using CKF feeds back the assisted code tracking loop, and the tracking loop has good performance, positioning accuracy and positioning stability.
Example two
FIG. 5 shows a block diagram of a MEMS-INS assisted GNSS vector loop tracking device, such as the MEMS-INS assisted GNSS vector loop tracking device of FIG. 5, comprising:
the signal acquisition module 501 is configured to acquire a digital intermediate frequency signal after the satellite signal is down-converted and quantized;
the code correlation module 502 is configured to mix the digital intermediate frequency signal with a signal generated by the carrier oscillator to obtain a receiving code, correlate the receiving code with a local replica code generated by the code generator, integrate and clear the receiving code to obtain six coherent integration results;
a first calculation module 503, configured to obtain a pseudo-range error and a pseudo-range rate error, and send the pseudo-range error and the pseudo-range rate error to a navigation filter of a global navigation satellite system to calculate current time rough position and speed information of a satellite navigation receiver;
a judging module 504, configured to judge whether the carrier-to-noise ratio meets a preset condition;
the CKF module 505 is configured to perform integrated navigation of the micro inertial navigation system and the global navigation satellite system by using a volume kalman filtering algorithm under the condition that the carrier-to-noise ratio does not meet a preset condition, and obtain accurate position and speed information of the satellite navigation receiver at the current moment by combining the rough position and speed information of the current moment;
a second calculating module 506, configured to calculate a pseudo range of the current time;
and the feedback module 507 is used for calculating the code frequency at the current moment and feeding back the code frequency to the code oscillator so as to enable the code generator to generate a local replica code and realize vector loop tracking.
Further, the code correlation module 502 correlates the digital intermediate frequency signal S IF When mixing with the signal generated by the carrier oscillator to obtain the receiving code, the method specifically comprises the following steps:
the in-phase carrier signal and the opposite-phase carrier signal generated by the carrier oscillator are respectively combined with the digital intermediate frequency signal S IF Mixing to obtain a receiving code, wherein the inverted carrier signal is subjected to 90-degree inversion and then mixed with the digital intermediate frequency signal.
Further, when the first calculation module 503 obtains the pseudo-range error and the pseudo-range rate error, the method specifically includes:
the code loop discriminator discriminates the code phase difference Deltaτ between the k-time received code and the locally replicated code k The code phase difference is subjected to linear conversion to obtain a pseudo-range error delta rho; a kind of electronic device with high-pressure air-conditioning system
Predicting the carrier frequency at time k+1 using a carrier loop discriminator (including a phase locked loop PLL), the carrier frequency f at time k+1 k+1 Carrier frequency f at time k k Is a difference Δf of (a) d Obtaining pseudo-range rate error through linear change
Further, when the CKF module 505 performs integrated navigation of the micro inertial navigation system and the global navigation satellite system by using the volumetric kalman filtering algorithm and combines the rough position and speed information at the current moment to obtain the accurate position and speed information at the current moment of the satellite navigation receiver, the method specifically includes:
setting volume points by spherical radial criteriaDefining the combined navigation state quantity as 19 dimensions, wherein the combined navigation state quantity comprises attitude errors phi in three directions, speed errors delta v in three directions, position errors delta p in three directions and zero offset drift epsilon of a gyro in three directions b Accelerometer random constant drift in three directions +.>Three-way MEMS-INS (including gyroscope and accelerometer) and GNSS lever arm position error δl b Setting the state initial value of the CKF filter as a zero matrix;
calculating the mean value of the one-step prediction state valueVariance P k+1/k ；
Decomposing the variance of the one-step prediction state value, and updating the volume point again;
calculating the mean of the one-step predictive measurements
Predicting the variance of the measurement values, and predicting the covariance of the state values and the one-step predicted measurement values; and
calculating the volume Kalman gain K k+1 Posterior mean of target statesPost-inspection prescriptionDifference P k+1 . The posterior mean value of the target state is calculated based on the rough position and the speed information at the current moment.
Further, when calculating the pseudo range of the current time, the second calculating module 506 directly calculates the pseudo range of the current time by combining the rough position and the speed information of the current time of the satellite navigation receiver under the condition that the carrier-to-noise ratio meets the preset condition. Under the condition that the carrier-to-noise ratio does not meet the preset condition, calculating the pseudo range of the current moment by combining the accurate position and speed information of the current moment of the satellite navigation receiver. Combining CKF predicted receiver position P r,k Calculating pseudo range rho of current moment k Combining the CKF predicted state quantity and the position and speed of the GNSS filter obtained in step S105, more accurate receiver position and speed information can be obtained.
The implementation content of each module function of the device in this embodiment may refer to the specific content of the first embodiment, and has all the beneficial effects of the first embodiment, which is not described herein.
Example III
The present embodiment provides a computer readable storage medium, on which a computer program is stored, which when executed by one or more processors, implements the MEMS-INS assisted GNSS vector loop tracking method of the first embodiment.
In this embodiment, the computer readable storage medium may be implemented by any type of volatile or nonvolatile Memory device or combination thereof, such as a static random access Memory (Static Random Access Memory, SRAM for short), an electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EPROM for short), a programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), a Read-Only Memory (ROM for short), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk. The details of the method are described in the first embodiment, and are not repeated here.
Example IV
The present embodiment provides an electronic device including a memory and one or more processors, where the memory stores a computer program that when executed by the one or more processors implements the MEMS-INS assisted GNSS vector loop tracking method of embodiment one.
In this embodiment, the processor may be an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), a digital signal processor (Digital Signal Processor, abbreviated as DSP), a digital signal processing device (Digital Signal Processing Device, abbreviated as DSPD), a programmable logic device (Programmable Logic Device, abbreviated as PLD), a field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), a controller, a microcontroller, a microprocessor, or other electronic component implementation for performing the method in the above embodiment. The method implemented when the computer program running on the processor is executed may refer to the specific embodiment of the method provided in the foregoing embodiment of the present invention, and will not be described herein. In actual practice, the electronic device may be a device that provides computing services.
In the embodiments provided in the embodiments of the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The system embodiments described above are merely illustrative.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications and variations of the invention be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (9)
1. A method for MEMS-INS assisted GNSS vector loop tracking, comprising:
acquiring a digital intermediate frequency signal after the satellite signal frequency-reducing quantization;
mixing the digital intermediate frequency signal with a signal generated by a carrier oscillator to obtain a receiving code, correlating the receiving code with a local replica code generated by a code generator, and obtaining six coherent integration results after integration and removal;
acquiring a pseudo-range error and a pseudo-range rate error, and sending the pseudo-range error and the pseudo-range rate error into a navigation filter of a global navigation satellite system to calculate the rough position and speed information of the current moment of a satellite navigation receiver;
judging whether the carrier-to-noise ratio meets a preset condition or not;
under the condition that the carrier-to-noise ratio does not meet the preset condition, the integrated navigation of the miniature inertial navigation system and the global navigation satellite system is performed by utilizing a volume Kalman filtering algorithm, and the accurate position and speed information of the current moment of the satellite navigation receiver are obtained by combining the rough position and speed information of the current moment, and the integrated navigation method comprises the following steps:
the method for carrying out integrated navigation of the miniature inertial navigation system and the global navigation satellite system by utilizing the volume Kalman filtering algorithm and obtaining the accurate position and speed information of the current moment of the satellite navigation receiver by combining the rough position and speed information of the current moment comprises the following steps:
defining combined navigation state quantity including attitude error, speed error, position error, gyro zero offset drift, lever arm position error of MEMS-INS and GNSS, accelerometer random offset drift and time asynchronous error, and setting CKF filter state initial value as zero matrix;
calculating the mean value and the variance of the one-step prediction state value;
decomposing the variance of the one-step prediction state value, and updating the volume point again;
calculating the average value of the one-step prediction measurement value;
predicting the variance of the measurement values, and predicting the covariance of the state values and the one-step predicted measurement values;
calculating the volume Kalman gain, the posterior mean value of the target state and the posterior variance;
the posterior mean value of the target state is calculated based on the rough position and the speed information at the current moment;
calculating a pseudo range of the current moment;
and calculating the code frequency at the current moment, and feeding back to a code oscillator so as to enable the code generator to generate a local replica code, thereby realizing vector loop tracking.
2. The MEMS-INS assisted GNSS vector loop tracking method of claim 1, wherein the mixing the digital intermediate frequency signal with the signal generated by the carrier oscillator to obtain the received code comprises:
and the in-phase carrier signal and the opposite-phase carrier signal generated by the carrier oscillator are respectively mixed with the digital intermediate frequency signal to obtain a receiving code, wherein the opposite-phase carrier signal is subjected to 90-degree opposite phase and then mixed with the digital intermediate frequency signal.
3. The MEMS-INS assisted GNSS vector loop tracking method of claim 1, wherein the obtaining pseudorange errors and pseudorange rate errors comprises:
the code ring discriminator discriminates the code phase difference between the k moment receiving code and the local copy code, and the code phase difference is linearly converted to obtain a pseudo-range error;
and predicting the carrier frequency at the moment k+1 by using a carrier ring discriminator, and obtaining a pseudo-range rate error by linear change of the carrier frequency at the moment k+1 and the carrier frequency difference value at the moment k.
4. The MEMS-INS assisted GNSS vector loop tracking method of claim 1, wherein after the calculating the code frequency at the current time, feeding back to a code oscillator to generate a local replica code, returning the digital intermediate frequency signal to mix with a signal generated by a carrier oscillator to obtain a received code, and correlating the received code with the local replica code generated by the code generator, integrating and removing the received code to obtain six coherent integration results.
5. The MEMS-INS assisted GNSS vector loop tracking method of claim 1, further comprising:
and under the condition that the carrier-to-noise ratio meets the preset condition, directly executing the pseudo range of the current moment and the code frequency of the current moment, and feeding back the pseudo range and the code frequency to a code oscillator so as to enable the code generator to generate a local replica code, thereby realizing the step of vector loop tracking.
6. The method of MEMS-INS assisted GNSS vector loop tracking of claim 1,
under the condition that the carrier-to-noise ratio meets the preset condition, calculating a pseudo range of the current moment by combining the rough position and the speed information of the current moment of the satellite navigation receiver;
and under the condition that the carrier-to-noise ratio does not meet the preset condition, calculating the pseudo range of the current moment by combining the accurate position and speed information of the current moment of the satellite navigation receiver.
7. A MEMS-INS assisted GNSS vector loop tracking apparatus comprising:
the signal acquisition module is used for acquiring digital intermediate frequency signals after the satellite signals are subjected to frequency reduction quantization;
the code correlation module is used for mixing the digital intermediate frequency signal with the signal generated by the carrier oscillator to obtain a receiving code, correlating the receiving code with a local copy code generated by the code generator, and obtaining six coherent integration results after integration and removal;
the first calculation module is used for acquiring pseudo-range errors and pseudo-range rate errors, and sending the pseudo-range errors and the pseudo-range rate errors into a navigation filter of a global navigation satellite system to calculate the current time rough position and speed information of the satellite navigation receiver;
the judging module is used for judging whether the carrier-to-noise ratio meets the preset condition;
the CKF module is used for carrying out combined navigation of the miniature inertial navigation system and the global navigation satellite system by utilizing a volume Kalman filtering algorithm under the condition that the carrier-to-noise ratio does not meet the preset condition, and obtaining the accurate position and speed information of the current moment of the satellite navigation receiver by combining the rough position and speed information of the current moment, and comprises the following steps:
setting a volume point through a spherical radial criterion, defining a combined navigation state quantity, wherein the combined navigation state quantity comprises an attitude error, a speed error, a position error, a gyro zero offset constant drift, a lever arm position error of MEMS-INS and GNSS, an accelerometer random constant drift and a time asynchronous error, and a CKF filter state initial value is set as a zero matrix;
calculating the mean value and the variance of the one-step prediction state value;
decomposing the variance of the one-step prediction state value, and updating the volume point again;
calculating the average value of the one-step prediction measurement value;
predicting the variance of the measurement values, and predicting the covariance of the state values and the one-step predicted measurement values;
calculating the volume Kalman gain, the posterior mean value of the target state and the posterior variance;
the posterior mean value of the target state is calculated based on the rough position and the speed information at the current moment;
the second calculation module is used for calculating the pseudo range of the current moment;
and the feedback module is used for calculating the code frequency at the current moment and feeding back the code frequency to the code oscillator so as to enable the code generator to generate a local copy code and realize vector loop tracking.
8. A computer readable storage medium having stored thereon a computer program which, when executed by one or more processors, implements a MEMS-INS assisted GNSS vector loop tracking method according to any of claims 1 to 6.
9. An electronic device comprising a memory and one or more processors, the memory having stored thereon a computer program that, when executed by the one or more processors, implements a MEMS-INS assisted GNSS vector loop tracking method according to any of claims 1 to 6.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2071831A1 (en) * | 1989-12-11 | 1991-06-12 | Christos T. Kyrtsos | Integrated vehicle positioning and navigation system, apparatus and method |
| US8370064B1 (en) * | 2010-04-14 | 2013-02-05 | The Boeing Company | Integrated global navigation satellite system and inertial navigation system for navigation and tracking |
| CN103116169A (en) * | 2013-01-20 | 2013-05-22 | 哈尔滨工程大学 | Anti-inference method based on vector tracking loop |
| CN103245963A (en) * | 2013-05-09 | 2013-08-14 | 清华大学 | Double-antenna GNSS/INS deeply integrated navigation method and device |
| CN104181574A (en) * | 2013-05-25 | 2014-12-03 | 成都国星通信有限公司 | Strapdown inertial navigation system/global navigation satellite system combined based navigation filter system and method |
| CN104931994A (en) * | 2015-06-12 | 2015-09-23 | 南京理工大学 | Software receiver-based distributed deep integrated navigation method and system |
| CN106443726A (en) * | 2016-08-30 | 2017-02-22 | 西安航天华迅科技有限公司 | GNSS vector tracking loop based on pre-filtering, and implementation method for GNSS vector tracking loop |
| CN106501832A (en) * | 2016-12-16 | 2017-03-15 | 南京理工大学 | A kind of fault-tolerant vector tracking GNSS/SINS deep integrated navigation methods |
| CN106980130A (en) * | 2017-03-03 | 2017-07-25 | 哈尔滨工程大学 | A kind of SINS/GNSS deep combinations adaptive navigation method |
| CN109307879A (en) * | 2018-11-08 | 2019-02-05 | 北京理工大学 | A kind of air navigation aid based on INS assisted GNSS vector tracking ring |
| CN109307878A (en) * | 2018-11-08 | 2019-02-05 | 北京理工大学 | A kind of air navigation aid of INS assisted GNSS scalar tracking ring |
| AR110651A1 (en) * | 2017-10-23 | 2019-04-17 | Deere & Co | CLOSED LOOP ARCHITECTURE OF KINETIC VECTOR PHASE IN REAL TIME (RTK) |
| CN111965683A (en) * | 2020-08-19 | 2020-11-20 | 上海海事大学 | Combined positioning method, device and storage medium for satellite positioning and inertial navigation positioning |
| CN112748449A (en) * | 2020-12-30 | 2021-05-04 | 上海海事大学 | Vector tracking method combining phase-locked loop and frequency-locked loop of satellite navigation receiver |
| CN112748450A (en) * | 2020-12-30 | 2021-05-04 | 上海海事大学 | Signal carrier loop tracking method of navigation satellite receiver |
| CN113848579A (en) * | 2021-11-29 | 2021-12-28 | 北京北斗华大科技有限公司 | Coarse error elimination method and system for INS assisted GNSS positioning |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6449559B2 (en) * | 1998-11-20 | 2002-09-10 | American Gnc Corporation | Fully-coupled positioning process and system thereof |
| CN106291645B (en) * | 2016-07-19 | 2018-08-21 | 东南大学 | The volume kalman filter method coupled deeply suitable for higher-dimension GNSS/INS |
| CN109991640B (en) * | 2017-12-29 | 2022-04-01 | 上海司南卫星导航技术股份有限公司 | Combined navigation system and positioning method thereof |
-
2022
- 2022-02-15 CN CN202210136906.0A patent/CN114485650B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2071831A1 (en) * | 1989-12-11 | 1991-06-12 | Christos T. Kyrtsos | Integrated vehicle positioning and navigation system, apparatus and method |
| US8370064B1 (en) * | 2010-04-14 | 2013-02-05 | The Boeing Company | Integrated global navigation satellite system and inertial navigation system for navigation and tracking |
| CN103116169A (en) * | 2013-01-20 | 2013-05-22 | 哈尔滨工程大学 | Anti-inference method based on vector tracking loop |
| CN103245963A (en) * | 2013-05-09 | 2013-08-14 | 清华大学 | Double-antenna GNSS/INS deeply integrated navigation method and device |
| CN104181574A (en) * | 2013-05-25 | 2014-12-03 | 成都国星通信有限公司 | Strapdown inertial navigation system/global navigation satellite system combined based navigation filter system and method |
| CN104931994A (en) * | 2015-06-12 | 2015-09-23 | 南京理工大学 | Software receiver-based distributed deep integrated navigation method and system |
| CN106443726A (en) * | 2016-08-30 | 2017-02-22 | 西安航天华迅科技有限公司 | GNSS vector tracking loop based on pre-filtering, and implementation method for GNSS vector tracking loop |
| CN106501832A (en) * | 2016-12-16 | 2017-03-15 | 南京理工大学 | A kind of fault-tolerant vector tracking GNSS/SINS deep integrated navigation methods |
| CN106980130A (en) * | 2017-03-03 | 2017-07-25 | 哈尔滨工程大学 | A kind of SINS/GNSS deep combinations adaptive navigation method |
| AR110651A1 (en) * | 2017-10-23 | 2019-04-17 | Deere & Co | CLOSED LOOP ARCHITECTURE OF KINETIC VECTOR PHASE IN REAL TIME (RTK) |
| CN109307879A (en) * | 2018-11-08 | 2019-02-05 | 北京理工大学 | A kind of air navigation aid based on INS assisted GNSS vector tracking ring |
| CN109307878A (en) * | 2018-11-08 | 2019-02-05 | 北京理工大学 | A kind of air navigation aid of INS assisted GNSS scalar tracking ring |
| CN111965683A (en) * | 2020-08-19 | 2020-11-20 | 上海海事大学 | Combined positioning method, device and storage medium for satellite positioning and inertial navigation positioning |
| CN112748449A (en) * | 2020-12-30 | 2021-05-04 | 上海海事大学 | Vector tracking method combining phase-locked loop and frequency-locked loop of satellite navigation receiver |
| CN112748450A (en) * | 2020-12-30 | 2021-05-04 | 上海海事大学 | Signal carrier loop tracking method of navigation satellite receiver |
| CN113848579A (en) * | 2021-11-29 | 2021-12-28 | 北京北斗华大科技有限公司 | Coarse error elimination method and system for INS assisted GNSS positioning |
Non-Patent Citations (7)
| Title |
|---|
| A distributed GNSS/INS integrated navigation system in a weak signal environment;Liu, W., Gu, M., Mou, M., Hu, Y., & Wang, S;《Measurement Science and Technology》;第32卷(第11期);1-4 * |
| COMPASS/GPS组合导航系统定位精度分析;李金金;应士君;刘卫;《航海技术》(第03期);38-41 * |
| Decentralized INS/GNSS system with MEMS-grade inertial sensors using QR-factorized CKF;Nourmohammadi, H., & Keighobadi, J;《IEEE Sensors Journal》;第17卷(第11期);3278-3287 * |
| Dual mass MEMS gyroscope temperature drift compensation based on TFPF-MEA-BP algorithm;Cao, H., Cui, R., Liu, W., Ma, T., Zhang, Z., Shen, C., & Shi, Y;《Sensor Review》;第41卷(第2期);162-175 * |
| Improved cubature Kalman filter for GNSS/INS based on transformation of posterior sigma-points error;Cui B, Chen X and Tang X.;《IEEE Trans Signal Process》(第65期);2975–2987 * |
| 卫星导航系统的可控旁瓣二进制偏移载波调制研究;胡媛;刘卫;;《电子设计工程》(第11期);158-161 * |
| 基于矢量跟踪的MEMS-SINS/GNSS深组合导航系统;赵志鹏;王新龙;;《导航与控制》(第06期);52-58 * |
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