CN114660638A - Frequency-locked loop assisted vector phase locking loop system - Google Patents
Frequency-locked loop assisted vector phase locking loop system Download PDFInfo
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- 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
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- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The invention provides a frequency-locked loop assisted vector phase locking loop system, which comprises: the system comprises a vector phase locking loop VPLL and a frequency locking loop FLL, wherein the frequency locking loop FLL is used for assisting the vector phase locking loop VPLL and is used for locking signals when a receiver carrier does high-mobility motion and accurately tracking and measuring carrier signals when a user is in low dynamic state, so that the tracking error of the vector phase locking loop is reduced, and the tracking performance of a corresponding vector receiver is improved. The invention combines the two loops, not only exerts the advantage of accurate tracking of the VPLL of the vector phase locking loop, but also enhances the signal locking and tracking capability of the loop under the high dynamic environment to a certain extent due to the assistance of the vector tracking and the FLL of the frequency locking loop. The system has more accurate estimation performance and tracking performance.
Description
Technical Field
The invention relates to the technical field of navigation, in particular to a frequency-locked loop aided vector phase locking loop system.
Background
The carrier phase tracking in the vector phase locked loop VPLL supports centimeter or more accurate position location, which is two orders of magnitude higher than the accuracy of non-coherent tracking navigation signals in the differential mode. However, carrier phase tracking is more vulnerable than pseudo code and frequency tracking, especially in high dynamic and deep signal attenuation and blocking, and also in multipath environment, but if the VPLL is assisted by using the frequency locking loop FLL, the respective advantages of the FLL and the VPLL can be fully exerted, so that the receiver can tolerate the high dynamic stress of the user, has strong anti-interference performance, and improves the carrier tracking performance of the receiver.
In addition, the FLL generally uses a discriminator to extract the carrier frequency error, but the discriminator can only keep the linear relationship between the input and the output in a small interval of the argument, thereby hindering the improvement of the receiver performance, and if the carrier frequency is estimated by using a nonlinear filtering method, the linear interval can be increased.
Disclosure of Invention
Although the vector phase locking loop has many advantages of the vector loop, when a receiver is in a high dynamic environment, large speed and position errors are caused, and even signal locking is difficult. According to the method, firstly, a scalar tracking loop is used for receiving and processing signals, then the signals are switched to a vector tracking loop, and a state equation and an observation equation of a high dynamic model of the vector loop are established.
The technical means adopted by the invention are as follows:
a frequency locked loop assisted vector phase locked loop system comprising: the system comprises a vector phase locking loop VPLL and a frequency locking loop FLL, wherein the frequency locking loop FLL is used for assisting the vector phase locking loop VPLL and is used for locking signals when a receiver carrier does high-mobility motion and accurately tracking and measuring carrier signals when a user is in low dynamic state, so that the tracking error of the vector phase locking loop is reduced, and the tracking performance of a corresponding vector receiver is improved.
Further, when the frequency locked loop FLL assists the vector phase locked loop VPLL, the frequency locked loop FLL is independent of the vector phase locked loop VPLL, and does not affect the operation of the vector phase locked loop VPLL.
Further, the vector phase locked loop VPLL comprises an integrate and dump, a phase discriminator, a navigation filter, and a carrier phase estimate, wherein:
the integral cleaner eliminates high-frequency components and noise in the signal through a low-pass filter;
the phase discriminator uses coherent integration result IP(n) and QP(n) outputting a phase difference between the received signal and the local replica signal;
the navigation filter obtains the corrected value of each parameter estimated value at the current moment by adopting an SRCKF algorithm, and simultaneously outputs the estimated value of each parameter at the next moment;
and the carrier phase estimation is carried out according to the output result of the navigation filter.
Further, the frequency locked loop FLL includes a cross-product-point multiplication, an extended kalman filter, and a carrier NCO, wherein:
the cross multiplication and point multiplication are respectively carried out on the outputs of the I branch and the Q branch;
the extended Kalman filter estimates the input frequency;
and the carrier NCO finishes the copying work of sine carrier and cosine carrier.
Further, when the receiver is in a high dynamic state, the vector tracking loop model is greatly different from a non-high dynamic state, a jerk model of a high-speed high maneuvering target is used for modeling the high dynamic state, and the velocity, acceleration and jerk vectors of the receiver in the high dynamic state are assumed as follows:
V＝[Vx Vy Vz]
V′＝[Vx′ Vy′ Vz′],
V″＝[Vx″ Vy″ Vz″]，,
the state equation is as follows:
wherein, Xk＝[Lkx Lky Lkz Vkx Vky Vkz V′kx V′ky V′kz V″kx V″ky V″kz]T，Wk-1Is state disturbance noise.
Further, if the output of the carrier phase discriminator is selected as the observed quantity, the observation equation of the system is as follows:
Zk＝h(ΔXk)+Uk。
further, the navigation filter adopts a square root cubature kalman filtering algorithm SRCKF, and the specific steps of the implementation of the square root cubature kalman filtering algorithm SRCKF in the vector tracking loop are as follows:
step one, time updating:
firstly, the SRCKF algorithm is utilized to obtain a state estimation value through a given model
And square root of the state estimation error covariance matrix Sk-1|k-1Wherein
Hypothesis process noise WkAnd observe the noise UkIndependently of each other, Wk～N(0，Qk),Uk～N(0，Qk) (ii) a Initial value of process noise covariance Q 01, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) observed noise covariance initial value R0＝diag(10，10……10)2n×2n；
Volume points are calculated and propagated using a state equation, where a state transition matrix F is as follows:
calculating a state quantity predicted value
And the prediction error WkSquare root of covariance matrix of (1)k|k-1(ii) a Wherein SQ，k-1Represents Qk-1Factor of square root, i.e.
Qk-1Represents the prediction error Wk-1The covariance matrix of (2) corresponds to the user dynamics in the directions of x, y and z three axes;
step two, measurement updating:
calculating volume points, transmitting the volume points through an observation equation, and calculating a measurement predicted value;
to obtain SR，kAn updated value of (d);
and obtaining the updated value of the state quantity and the updated value of the square root factor of the state estimation error covariance matrix, and then entering the next cycle.
Compared with the prior art, the invention has the following advantages:
1. according to the vector phase locking loop system assisted by the frequency locking loop, the volume Kalman filtering CKF algorithm with higher numerical precision and stability is adopted in the loop navigation filter to replace the commonly used extended Kalman filtering EKF algorithm, but because the operation which possibly damages the symmetry and the normality of a covariance matrix exists in each iteration of the CKF algorithm, square root filtering is applied to the CKF, and the stability and the numerical precision of the filter are further improved. The adverse effects caused by weak signal channels are reduced.
2. The frequency-locked loop-assisted vector phase-locked loop system provided by the invention has more accurate estimation performance and tracking performance, through quantitative evaluation, the tracking performance of the FLL-assisted VPLL loop realized based on the SRCKF algorithm is improved by about 25% on average compared with the FLL-assisted PLL loop realized based on the SRCKF algorithm, and the tracking precision and tracking performance of the FLL-assisted VPLL loop are superior to those of the FLL-assisted PLL loop under the same external condition.
Based on the reason, the method can be widely popularized in the fields of navigation and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the system of the present invention.
Fig. 2 is a high dynamic motion curve of an acceleration signal of a receiver according to an embodiment of the present invention.
Fig. 3 is a high dynamic motion curve of a jerk signal of a receiver according to an embodiment of the present invention.
Fig. 4 is a graph of RMS frequency error versus carrier-to-noise ratio CNR for channel 2 according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of a position error according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a speed error according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus that are known by one of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. Any specific values in all examples shown and discussed herein are to be construed as exemplary only and not as limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
In the description of the present invention, it is to be understood that the orientation or positional relationship indicated by the directional terms such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal" and "top, bottom", etc., are generally based on the orientation or positional relationship shown in the drawings, and are used for convenience of description and simplicity of description only, and in the absence of any contrary indication, these directional terms are not intended to indicate and imply that the device or element so referred to must have a particular orientation or be constructed and operated in a particular orientation, and therefore should not be considered as limiting the scope of the present invention: the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.
Spatially relative terms, such as "above … …," "above … …," "above … … surface," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is turned over, devices described as "above" or "on" other devices or configurations would then be oriented "below" or "under" the other devices or configurations. Thus, the exemplary term "above … …" can include both an orientation of "above … …" and "below … …". The device may be otherwise variously oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of the present invention should not be construed as being limited.
The invention provides a frequency-locked loop assisted vector phase locking loop system, which comprises: the system comprises a vector phase locking loop VPLL and a frequency locking loop FLL, wherein the frequency locking loop FLL is used for assisting the vector phase locking loop VPLL and is used for locking signals when a receiver carrier does high-mobility motion and accurately tracking and measuring carrier signals when a user is in low dynamic state, so that the tracking error of the vector phase locking loop is reduced, and the tracking performance of a corresponding vector receiver is improved.
As shown in fig. 1, the vector phase lock loop VPLL comprises an integrate and dump, a phase discriminator, a navigation filter, and a carrier phase estimate, wherein:
the integral cleaner eliminates high-frequency components and noise in the signal through a low-pass filter;
the phase discriminator uses coherent integration result IP(n) and QP(n) outputting a phase difference between the received signal and the local replica signal;
the navigation filter obtains a correction value of each parameter estimation value at the current moment by adopting an SRCKF algorithm, and outputs the estimation value of each parameter at the next moment;
and the carrier phase estimation is carried out according to the output result of the navigation filter.
As shown in fig. 1, the frequency locked loop FLL includes a cross-point multiplication, an extended kalman filter, and a carrier NCO, where:
the cross multiplication and point multiplication are respectively carried out on the outputs of the I branch and the Q branch;
the extended Kalman filter estimates the input frequency;
and the carrier NCO finishes the copying work of sine carrier and cosine carrier.
In specific implementation, as a preferred embodiment of the present invention, when the frequency locked loop FLL assists the vector phase locked loop VPLL, the frequency locked loop FLL is independent of the vector phase locked loop VPLL, and does not affect the operation of the vector phase locked loop VPLL.
In specific implementation, as a preferred embodiment of the present invention, when the receiver is in a high dynamic state, the vector tracking loop model is greatly different from the non-high dynamic state, and the high dynamic state is modeled by using a jerk model of the high-speed and high-maneuvering target, assuming that the velocity, acceleration, and jerk vectors of the receiver in the high dynamic state are as follows:
V＝[Vx Vy Vz]，
V′＝[Vx′ Vy′ Vz′]，,
V″＝[Vx″ Vy″ Vz″]，,
the state equation is as follows:
wherein, Xk＝[Lkx Lky Lkz Vkx Vky Vkz V′kx V′ky V′kz V″kx V″ky V″kz]T，Wk-1Is state disturbance noise. The jerk model is additionally provided with one dimension on the basis of the acceleration model, namely the jerk can be estimated, so that the acceleration parameter can be estimated more accurately, and the jerk model is very suitable for modeling a high-dynamic carrier.
In specific implementation, as a preferred embodiment of the present invention, if the output of the carrier phase discriminator is selected as the observed quantity, the observation equation of the system is as follows:
Zk＝h(ΔXk)+Uk (2)。
in specific implementation, as a preferred implementation of the present invention, the navigation filter employs a square root cubature kalman filter algorithm SRCKF, and the implementation of the square root cubature kalman filter algorithm SRCKF in the vector tracking loop specifically includes the following steps:
step one, time updating:
firstly, the SRCKF algorithm is utilized to obtain a state estimation value through a given model
And square root of the state estimation error covariance matrix Sk-1|k-1Wherein
Hypothesis process noise WkAnd observe the noise UkIndependently of each other, Wk～N(0，Qk),Uk～N(0，Qk) (ii) a Initial value of process noise covariance Q 01, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) observation noiseInitial value of covariance R0＝diag(10，10……10)2n×2n；
Volume points are calculated and propagated using a state equation, where a state transition matrix F is as follows:
calculating a state quantity predicted value
And the prediction error WkSquare root of covariance matrix of (1)k-1|k-1(ii) a Wherein SQ，k-1Represents Qk-1Factor of square root, i.e.
Qk-1Represents the prediction error Wk-1The covariance matrix of (2) corresponds to the user dynamics in the directions of x, y and z three axes;
step two, measurement updating:
calculating volume points, transmitting the volume points through an observation equation, and calculating a measurement predicted value;
to obtain SR，kAn updated value of (d);
and obtaining the updated value of the state quantity and the updated value of the square root factor of the state estimation error covariance matrix, and then entering the next cycle.
In conclusion, in order to improve the tracking performance of the signal under the high dynamic stress of the VPLL, the FLL is used for assisting the VPLL, has a wider noise bandwidth, can tolerate the high dynamic stress of a user more robustly, and can track the signal with a lower signal-to-noise ratio, but the loop noise of the FLL is higher, and the tracking of the signal is not accurate enough, and the two loops are combined, so that the advantage of accurate tracking of the VPLL loop is exerted, and the locking and tracking capabilities of the loop on the signal under the high dynamic environment are enhanced to a certain extent due to the vector tracking and the assistance of the FLL.
Examples
In order to verify the effectiveness of the system, a simulation experiment is carried out, in the experiment, a HWA-RNSS-7300 satellite navigation signal simulator of Beijing Huali Chutong science and technology limited company is adopted to generate a Beidou satellite navigation signal required by the experiment, an intermediate frequency data collector of a satellite source Beidou navigation technology limited responsibility company is used for carrying out down-conversion on a signal output by the simulator into an intermediate frequency signal, and the output intermediate frequency signal fIF4.092MHz, sampling frequency fsThe number of sample bits is 2 bits at 16.368 MHz. The receiver adopts a Beidou vector software receiver, the pre-detection integration time is 1ms, and the tracking threshold is 35 dB/Hz. Because it is difficult to generate a true jerk signal and a large magnitude acceleration signal in real life, a highly dynamic model of Jet Propulsion Laboratory (JPL) laboratories, usa, is used to simulate the motion state of a receiver.
The highly dynamic motion of the receiver relative to the satellite will follow fig. 2 and 3. Fig. 2 is a high dynamic motion curve of an acceleration signal of a receiver, fig. 3 is a high dynamic motion curve of a jerk signal, and the simulation time is 8 s. Initially the jerk of the receiver is zero and the receiver is making a uniform acceleration movement at an acceleration of-25 g, but at 3s the jerk increases abruptly to 100g/s and lasts for 0.5s, at which time the acceleration of the receiver becomes 25g and makes a uniform acceleration movement at an acceleration of 25g for 2s, at 5.5s the jerk again becomes abruptly-100 g/s and lasts for 0.5s, at which time the acceleration becomes-25 g and makes a uniform acceleration movement therewith.
For the above-mentioned high dynamic model, which is modeled herein using a jerk model, the process equation and the observation equation are respectively equations (1) and (2), the process noise covariance:
wherein
Denotes the variance of Y (k), Y (t) denotes the fourth derivative of the position X (t), and the observed noise covariance matrix is as follows:
R＝diag(Rcode，1，Rcarrier，1………Rcode，n，Rcarrier，n)2n×2n
firstly, taking the root mean square error of frequency as an evaluation index, and obtaining a relation curve of the RMS frequency error of a channel and a carrier-to-noise ratio (CNR) through 500 Monte Carlo experiments, wherein RMSE is defined as follows:
wherein, Xn(k) And
representing the true and filtered estimates at the same time.
The movement of the carrier is as follows: firstly, the number of channels of a signal is 12 in a period of 0s-25s, the carrier does uniform linear motion in the period, then in a period of 26s-120s, the number of channels of the signal is reduced to three or less, namely the carrier is in a weak signal environment at the moment, the carrier still does uniform linear motion in a period of 26s-60s, then in a period of 60 s-85 s, the carrier periodically does high dynamic motion as shown in fig. 3, at the moment, the receiver is in an extremely severe high dynamic weak signal environment, and the number of channels of the signal is restored to 12 again and does uniform linear motion after 120 s.
FIG. 4 is a plot of RMS frequency error versus carrier-to-noise ratio CNR for channel 2, where the frequency estimate for channel 2 is obtained by multiplying the speed estimate of the receiver by the scaling factor μ; as can be seen from FIG. 4, the frequency-locked loop assisted vector phase-locked loop FLL assisted VPLL has a significant improvement in frequency tracking accuracy when compared to the frequency-locked loop assisted phase-locked loops FLL assisted PLL and VPLL, when C/N is used0When the frequency is 21.5, the tracking precision of the FLL asserted VPLL is improved by 6dB compared with the FLL asserted PLL and is improved by 9dB compared with the VPLL, and C/N is increased0Frequency estimation mean square error of FLL asserted VPLL at 22.5At 33Hz, it is improved by 5dB compared with FLL asserted PLL and by 10dB compared with VPLL, but with carrier to noise ratio C/N0The improvement is gradually reduced.
As can be seen from fig. 5, the VPLL tracking loop performs well in the first 25s tracking period, but the position error and the velocity error increase greatly during 26s-120s, and the difference between the tracking performance and the other two loops also increases greatly, and the tracking performance deteriorates further during 60-85s with the high dynamic motion of the receiver. And the number of channels with signals is restored to 12 again after 120s, the position error and the speed error of the VPLL loop are both greatly reduced at the moment, but the tracking state in the period from 0s to 25s still can not be restored, the maximum position error difference from the FLL associated VPLL at the moment is 134.5m, and the maximum speed error difference is 7.91 m/s.
Simulation results show that when the number of signal channels is three or less, or when a carrier moves in a high dynamic state on the basis of the three or less, the FLL-assisted VPLL loop shows lower position error, lower speed error and higher filtering precision compared with the FLL-assisted PLL loop and the pure VPLL loop, and the FLL-assisted VPLL loop and the FLL-assisted PLL loop can achieve fast re-tracking when the number of channels with signals is restored to four or more, and the VPLL loop is improved greatly only when the number of channels with signals is high dynamic and weak signals or weak signals, but has a gap compared with the other two loops. And through quantitative evaluation, the tracking performance of the FLL-assisted VPLL loop realized based on the SRCKF algorithm is improved by about 25% on average compared with the FLL-assisted PLL loop realized based on the SRCKF algorithm, the tracking precision and the tracking performance of the FLL-assisted VPLL loop are superior to those of the FLL-assisted PLL loop under the same external condition, and in sum, the FLL-assisted VPLL loop in the three loops has more accurate estimation performance and tracking performance.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A frequency locked loop assisted vector phase locked loop system, comprising: the system comprises a vector phase locking loop VPLL and a frequency locking loop FLL, wherein the frequency locking loop FLL is used for assisting the vector phase locking loop VPLL and is used for locking signals when a receiver carrier does high-mobility motion and accurately tracking and measuring carrier signals when a user is in low dynamic state, so that the tracking error of the vector phase locking loop is reduced, and the tracking performance of a corresponding vector receiver is improved.
2. The frequency-locked loop assisted vector phase-locked loop system of claim 1, wherein when the frequency-locked loop FLL assists the vector phase-locked loop VPLL, the frequency-locked loop FLL is independent of the vector phase-locked loop VPLL without affecting the operation of the vector phase-locked loop VPLL.
3. The frequency locked loop assisted vector phase locked loop system of claim 1, wherein the vector phase locked loop VPLL comprises integrate and dump, phase discriminator, navigation filter, and carrier phase estimation, wherein:
the integral cleaner eliminates high-frequency components and noise in the signal through a low-pass filter;
the phase discriminator uses coherent integration result IP(n) and QP(n) outputting a phase difference between the received signal and the local replica signal;
the navigation filter obtains the corrected value of each parameter estimated value at the current moment by adopting a square root cubature Kalman filtering SRCKF algorithm, and simultaneously outputs the estimated value of each parameter at the next moment;
and the carrier phase estimation is carried out according to the output result of the navigation filter.
4. The frequency-locked loop assisted vector phase-locked loop system of claim 1, wherein the frequency-locked loop FLL comprises a cross-product multiplication, an extended kalman filter, and a carrier NCO, wherein:
the cross multiplication and point multiplication are respectively carried out on the outputs of the I branch and the Q branch;
the extended Kalman filter estimates the input frequency;
and the carrier NCO finishes the copying work of sine carrier and cosine carrier.
5. The frequency-locked loop assisted vector phase-locked loop system of claim 1, wherein when the receiver is in a high dynamic state, the vector tracking loop model is very different from the non-high dynamic state, and the high dynamic state is modeled by using a jerk model of a high-speed high-mobility target, and the velocity, acceleration and jerk vectors of the receiver in the high dynamic state are assumed as follows:
V＝[Vx Vy Vz]，
V′＝[Vx′ Vy′ Vz′]，,
V″＝[Vx″ Vy″ Vz″]，,
the state equation is as follows:
wherein Xk＝[Lkx Lky Lkz Vkx Vky Vkz V′kx V′ky V′kz V″kx V″ky V″kz]T，Wk-1Is state disturbance noise.
6. The frequency-locked loop assisted vector phase-locked loop system of claim 2, wherein if the output of the carrier phase discriminator is selected as the observed quantity, the system's observation equation is as follows:
Zk＝h(ΔXk)+Uk。
7. the frequency-locked loop assisted vector phase-locked loop system of claim 2, wherein the navigation filter employs a square root volumetric kalman filter algorithm (SRCKF), and the implementation of the square root volumetric kalman filter algorithm (SRCKF) in the vector tracking loop comprises the following specific steps:
step one, time updating:
firstly, the SRCKF algorithm is utilized to obtain a state estimation value through a given model
And square root of the state estimation error covariance matrix Sk-1|k-1In which
Hypothesis of Process noise WkAnd observe the noise UkIndependently of each other, Wk～N(0，Qk),Uk～N(0，Qk) (ii) a Initial value of process noise covariance Q0Observed noise covariance initial value R ═ diag (1, 1, 1, 1, 1, 1, 1, 1, 1), and0＝diag(10，10……10)2n×2n；
volume points are calculated and propagated using a state equation, where a state transition matrix F is as follows:
calculating a state quantity predicted value
And the prediction error WkSquare root of covariance matrix of (1)k|k-1(ii) a Wherein SQ，k-1Represents Qk-1Factor of square root, i.e.
Qk-1Represents the prediction error Wk-1The covariance matrix of (2) corresponds to the user dynamics in the directions of x, y and z three axes;
step two, measurement updating:
calculating volume points, transmitting the volume points through an observation equation, and calculating a measurement predicted value;
to obtain SR，kAn updated value of (d);
and obtaining the updated value of the state quantity and the updated value of the square root factor of the state estimation error covariance matrix, and then entering the next cycle.
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