CN107659393B - Multi-PLL carrier tracking loop capable of effectively weakening ionosphere scintillation effect - Google Patents

Multi-PLL carrier tracking loop capable of effectively weakening ionosphere scintillation effect Download PDF

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CN107659393B
CN107659393B CN201710694705.1A CN201710694705A CN107659393B CN 107659393 B CN107659393 B CN 107659393B CN 201710694705 A CN201710694705 A CN 201710694705A CN 107659393 B CN107659393 B CN 107659393B
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祝雪芬
徐斌铖
陈熙源
汤新华
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Southeast University
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Abstract

The invention provides a multi-PLL carrier tracking loop capable of effectively weakening the ionospheric scintillation effect. The method sets a plurality of parallel PLLs with the same structure and different parameters in a single channel, sets and calculates the correlation and the compatibility to select an effective sub-loop and the output estimation thereof, and reduces the dependency of the loop performance on the loop parameters; the feedback of each sub-loop is determined through a tracking fusion algorithm, so that the risk of losing lock of a single loop is reduced; the invention effectively improves the reliability and the output continuity of a carrier tracking loop under the condition of ionosphere flicker, and provides possibility for keeping tracking of signals and improving positioning accuracy.

Description

Multi-PLL carrier tracking loop capable of effectively weakening ionosphere scintillation effect
Technical Field
The invention relates to the technical field of wireless communication, in particular to a multi-PLL carrier tracking loop capable of effectively weakening the ionospheric scintillation effect.
Background
The GPS signal is subject to a number of error factors as it propagates from the satellite to the receiver, the most significant of which is the error caused by ionospheric flicker. When a radio signal passes through an ionized layer, the amplitude and the phase of the signal are greatly jittered due to the uneven electron density distribution of the ionized layer, which can cause a carrier phase-locked loop of a GPS receiver to lose the lock on the signal. Ionospheric scintillation poses a certain threat to the reliability and accuracy of GPS received signals, and the navigation positioning error is increased and even the navigation is interrupted due to the slippage of a phase-locked loop.
In order to reduce the loss of lock caused by ionospheric flicker, PLL algorithms based on kalman filtering, tracking algorithms based on vectors, etc. have been proposed. The kalman filter-based PLL algorithm uses a kalman filter instead of the low-pass filter, and thus it has a varying bandwidth. In the case of ionosphere scintillation, the stability of the method is better than that of a traditional third-order PLL, but the performance of the method is greatly influenced by bandwidth and integration time, the requirements on a process model and a noise model are high, and in a practical situation, the models are difficult to accurately establish. Vector-based tracking algorithms use observations of all visible channels to estimate the carrier phase or doppler shift of the respective channel, channels affected by ionospheric flicker can be corrected with unaffected channel signals, while channels affected by ionospheric flicker can in turn contaminate healthy channels. Since the performance of the tracking loop is affected by the loop parameters (noise bandwidth, correlation integration time, etc.), the loop parameters are set to correspond to the ionospheric scintillation intensity, but in the case of ionospheric scintillation, these parameters are difficult to estimate, which limits the reliability of these methods.
Disclosure of Invention
In order to solve the existing problems, the invention provides a multi-PLL carrier tracking loop structure capable of effectively weakening the influence of ionospheric scintillation. The structure sets a plurality of parallel PLLs with different parameters in a single channel, the stability of the structure depends on the fusion algorithm of all sub-loops, the dependency of the loop performance on the loop parameters is reduced, and the stability and the reliability of the loop are improved at the same time, so as to achieve the aim, the invention provides a multi-PLL carrier tracking loop capable of effectively weakening the ionospheric scintillation effect, which comprises the following steps:
step A: by proximity deltanmThe size determines the correlation between different sub-loops, and a threshold value delta is set0The compatibility gamma is obtained by distinguishing and selecting loosely coupled sub-loops with different performances and performing correlation operation on the output error and the variance of the error of the sub-loopsnm(k) To determine the validity of the sub-loop output;
and B: taking the integration time of the current sub-loop as a standard, sampling the integration time of other sub-loops upwards or downwards to determine the output with uniform integration time, judging the stability of the output of the sub-loop according to the compatibility, and estimating the feedback of the sub-loop according to the stability principle;
and C: and selecting a weight coefficient according to the principle of minimum error to perform weighted average on the feedback of each sub-loop, and integrating redundant measurement data to obtain a continuous and accurate final output value.
In a further development of the invention, in step A, δ is determinednmAnd gammanm(k) The specific process of the calculation formula and the selection basis of the sub-loop thereof is as follows:
step A-1: selecting loosely coupled sub-loops with different properties, using closeness deltanmTo describe the correlation between different sub-loops:
Figure BDA0001378816270000021
wherein upsilon isn(k) To be the output error of the sub-loop n,
Figure BDA0001378816270000022
setting a threshold delta for the variance of the sub-loop n-errors00.5, selecting the closeness degree deltanmLess than threshold delta0The loosely coupled sub-loop of (a);
step A-2: subtracting the Doppler frequency shift of the two sub-loops in the kth sampling period to obtain an error term epsilonnm(k) The specific process is as follows:
εnm(k)＝ωD,n(k)-ωD,m(k)＝υn(k)-υm(k),(m＝1,...,Nandm≠n)；
then the compatibility can be expressed as:
Figure BDA0001378816270000023
wherein, γnm(k) Has a value range of [0,1 ]]，γnm(k) Greater than 0 indicates that the sub-loops n and m are compatible with each other, γ, in the kth sampling periodnm(k) A value equal to 0 indicates that the sub-loops n and m oppose each other, and the output result is unreliable when the sub-loops n oppose the total number of 2/3.
In step B, the output of the sub-loop is determined by a tracking fusion algorithm, the integral time of each sub-loop is unified, and then the feedback result is determined by a stability principle, and the specific process is as follows:
step B-1: preprocessing to unify integration time with integration time T of the current sub-loopcoh,nAs a reference standard, for example, the integration time T of the other sub-loops is calculated by the following algorithmcoh,mConversion to Tcoh,nThe specific process comprises the following steps:
if Tcoh,m＞Tcoh,nThen, upsampling:
ωD,m(kn+l)＝ωD,m(km)；
wherein k isn＝Mk m1, M-1 and
Figure BDA0001378816270000031
rounding M;
if Tcoh,m＜Tcoh,nThen, down-sampling:
Figure BDA0001378816270000032
wherein,
Figure BDA0001378816270000033
rounding M;
step B-2: calculating the compatibility of the sub-loop according to gammanm(k) The number greater than 0 determines the stability of the sub-loop according to the following:
if it is
Figure BDA0001378816270000034
Greater than 1/3 of the total number, the output of the sub-loop is stable and its feedback is:
Figure BDA0001378816270000035
if it is
Figure BDA0001378816270000036
Is less than 1/3 of the total number, the output of the sub-loop is unstable, and the sub-loop output with the least noise strength is selected as the feedback of the sub-loop:
Figure BDA0001378816270000037
γii(k)≥γmm(k) i, m ≠ N, and i, m ≠ N
Wherein gamma isii(k) The compatibility when n ═ m is shown, which reflects the measured noise level of the sub-loop i.
In step C, the redundant data is integrated by an output fusion algorithm to obtain a final output estimate, and the specific process is as follows:
and C: and carrying out weighted average on the redundant data, wherein the weighting principle is as follows: presence weight coefficient vector wTSuch that the following equation is minimized:
Jw＝wTQ1w-Q2w；
wherein
Figure BDA0001378816270000038
An NxN order covariance matrix representing two different sub-loop measurements;
Figure BDA0001378816270000039
the measurement uncertainty vector is represented. q. q.s1,nmAnd q is2,nCan be calculated by the following formula:
q1,nm＝E[εn(k)εm(k)]；
Figure BDA00013788162700000310
the final output results are:
Figure BDA0001378816270000041
wherein,
Figure BDA0001378816270000042
representing the measurement vector.
The invention has the beneficial effects that: the invention provides a multi-PLL carrier tracking loop capable of effectively weakening the ionospheric scintillation effect. The method sets and calculates the correlation and compatibility to select effective parallel sub-loops, reduces the dependency of loop performance on loop parameters, determines the feedback of each sub-loop through a tracking fusion algorithm, reduces the risk of losing lock of a single loop, integrates redundant data through an output fusion algorithm, and improves the continuity and accuracy of output. The invention effectively improves the reliability and the output continuity of the carrier tracking loop under the condition of ionosphere flicker, and provides possibility for keeping tracking of signals and improving positioning accuracy.
Drawings
Fig. 1 is a schematic diagram of the structure of a multi-PLL carrier tracking loop of the present invention.
FIG. 2 is a schematic diagram of the structure of the tracking fusion algorithm of the present invention.
Detailed Description
The invention is described in further detail below with reference to the following detailed description and accompanying drawings:
the invention provides a multi-PLL carrier tracking loop structure capable of effectively weakening the influence of ionospheric scintillation. The structure sets a plurality of parallel PLLs with different parameters in a single channel, the stability of the structure depends on the fusion algorithm of all sub-loops, the dependency of the loop performance on the loop parameters is reduced, and the stability and the reliability of the loop are improved.
The invention implements a multi-PLL carrier tracking loop, the structure of which is shown in figure 1, and parallel PLLs have the same loop structure: i.e. each sub-loop has its own loop discriminator, filter and digital controlled oscillator. In addition, the Doppler frequency shift output of the current sub-loop and the other sub-loops is subjected to tracking fusion algorithm to obtain a reliable feedback value, the reliable feedback value is input into the loop discriminator through integration, and the feedback of each sub-loop is subjected to output fusion algorithm to obtain final position estimation.
Step A: by proximity deltanmThe size determines the correlation between different sub-loops, and a threshold value delta is set0The compatibility gamma is obtained by distinguishing and selecting loosely coupled sub-loops with different performances and performing correlation operation on the output error and the variance of the error of the sub-loopsnm(k) To determine the validity of the sub-loop output;
before determining correlation and compatibility, an estimation is made of the output error model of the tracking loop, where an assumption is made about the multi-PLL structure model.
Assume that 1: the factor loops have the same structure, so when the loop only has a single independent PLL, no additional information is used for judging the correlation of the PLL, and when the loop only has two PLL paths and the difference is found to be large by measurement, the loop is difficult to judge which path is reliable, therefore, the invention sets at least 3 PLL paths to form the structure of the multi-PLL.
Assume 2: true value of Doppler shift in a short time interval
Figure BDA0001378816270000051
An unbiased estimate can be made with a polynomial of order 2 with respect to t (k):
Figure BDA0001378816270000052
wherein,
Figure BDA0001378816270000053
is that
Figure BDA0001378816270000054
Unbiased estimation of (2); a is0(k)，a1(k)，a2(k) Is the correlation coefficient, t (K) is the time of the kth sampling period, usually a short-term unbiased estimated polynomial holds, and the magnitude of the sampling frequency is related to the doppler shift: in a static state, the Doppler frequency shift changes slowly so that the sampling frequency can be set to be smaller; under dynamic conditions, the sampling frequency should be increased to accommodate the rapidly changing doppler shift.
Assume that 3: the measured noise model for Doppler shift may be used with a mean of 0 and a variance of
Figure BDA0001378816270000055
The white gaussian noise is estimated, and the doppler frequency shift measured by the sub-loop is:
Figure BDA0001378816270000056
wherein upsilon isn(k) Is noise of the sub-loop n.
If it is
Figure BDA0001378816270000057
Approach to true value
Figure BDA0001378816270000058
Then the noise v of the sub-loop nn(k) Can be written as:
Figure BDA0001378816270000059
noise vn(k) The mean and variance of (a) are:
Figure BDA00013788162700000510
Figure BDA00013788162700000511
step A-1: because the structures and the measured values of the sub-loops are similar, namely, the sub-loops have certain coupling performance, the deeply coupled PLL tends to have more similar output, and when strong flicker occurs in an ionosphere, the sub-loops can lose the locking of signals. Therefore, it is critical to choose loosely coupled PLLs with different output characteristics. Here using the closeness δnmTo describe the correlation between different sub-loops:
Figure BDA00013788162700000512
wherein,
Figure BDA00013788162700000513
is upsilonn(k) The variance of (a); deltanm＝δmnAnd its size is [0,1 ]]Within the interval; variance (variance)
Figure BDA00013788162700000514
Influenced by system parameters and environment; when deltanmWhen 1, indicating deep coupling between sub-loops n and m with the same uncertainty; when deltanmWhen 0, it indicates that the sub-loops n and m are independent of each other and have completely uncorrelated uncertainties；
Setting a threshold value delta0Determining the correlation r between different PLLsnmTo determine the selected decoupled sub-loop:
Figure BDA0001378816270000061
when deltannGreater than a threshold value delta0When r isnm1, two PLLs are coupled; when deltannLess than threshold delta0When r isnmTo 0, the two PLLs are decoupled. In the present invention, δ is set0Is 0.5, deltannHalf of the maximum value.
Step A-2: the difference between the doppler shift measurements for the two different sub-loops is:
εnm(k)＝ωD,n(k)-ωD,m(k)＝υn(k)-υm(k),(m＝1,...,Nandm≠n)
since the invention selects a decoupled PLL in the loop, the noise upsilon is measuredn(k) And upsilonm(k) Not related; from the assumption of 2, εnm(k) Subject to a positive-Taiwan distribution, its mean and variance are:
E[εnm(k)]＝E[υn(k)-υm(k)]＝E[υn(k)]-E[υm(k)]＝0
Figure BDA0001378816270000062
the compatibility is set as:
Figure BDA0001378816270000063
wherein, γnm(k) The size is in the interval of [0,1 ]]And (4) the following steps. When gamma isnm(k)>At 0, in the kth sampling period, the sub-loops n and m are compatible, namely the states of the two sub-loops are the same and the measured value is reliable; if gamma isnm(k) The states of sub-loops n and m are opposite, and 1 or 2 measurements in both sub-loops are unreliable; when the sub-loop n exceeds the total number 2-3, its output is unreliable when the sub-loop states are opposite;
in particular, when n ═ m, the error is:
Figure BDA0001378816270000064
its autocorrelation compatibility can be written as:
Figure BDA0001378816270000065
when in use
Figure BDA0001378816270000066
Reliable time, gammann(k) Indicating the measured noise intensity. Smaller gammann(k) Represents a large tracking error as gammann(k) When the value is equal to 0, the sub-loop n is unlocked, and the output is unreliable;
in step B, the structure of the tracking fusion algorithm of the sub-loop n is shown in fig. 2; the different sub-loops having different sampling periods, their magnitudes and integration times TcohCorrelation; preprocessing Doppler frequency shift measurement values of other sub-loops by taking the current sub-loop n as a reference to obtain the same integration time; simultaneous calculation of omegaD,n(k) Estimated
Figure BDA0001378816270000071
Calculating the output of the sub-loop by a tracking fusion algorithm; the specific process is as follows:
step B-1: the integral time of branch n is Tcoh,nIntegration time of the other branches is Tcoh,m(ii) a If Tcoh,m＝Tcoh,nThen no pretreatment is needed; otherwise, the pretreatment can be carried out in two cases, and the specific process is as follows:
if Tcoh,m＞Tcoh,nThen the pre-processing can be written as:
ωD,m(kn+l)＝ωD,m(km)
wherein k isn＝Mkm,l＝0,1,...,M-1And is
Figure BDA0001378816270000072
And rounding by M. The function of this preprocessing is to up-sample the sub-loop output. Doppler shift omegaD,nSampling frequency of
Figure BDA0001378816270000073
Grow to
Figure BDA0001378816270000074
Its noise vm(kn) The characteristics of (A) are as follows:
E[υm(kn)]＝E[υm(km)]＝0
Figure BDA0001378816270000075
if Tcoh,m＜Tcoh,nThen the preprocessing is to down-sample the sub-loop output:
Figure BDA0001378816270000076
wherein,
Figure BDA0001378816270000077
and rounding by M. In this case, the noise vm(kn) The characteristics of (A) are as follows:
Figure BDA0001378816270000078
Figure BDA0001378816270000079
in the case of the assumption 3 that,
Figure BDA00013788162700000710
can be expressed by a quadratic polynomial; its recursive form is:
Figure BDA00013788162700000711
(kest-1)Test≤knTcoh,n＜kestTest
wherein,
Figure BDA0001378816270000081
as a sampling frequency of
Figure BDA0001378816270000082
An output estimate of time; a is1(kest-1) and a2(kest-1) for each TestThe updated adjustable coefficient is obtained; the coefficient can be obtained by processing the output phase by using a least square method; after the update of the coefficients, the coefficients are updated,
Figure BDA0001378816270000083
the estimation can be performed by the above formula until the next update time;
step B-2: the tracking fusion algorithm uses the compatibility to determine the stability of the sub-loop to determine loop feedback; for a sub-loop, if γnmA number > 0 i.e.
Figure BDA0001378816270000084
Beyond 1/3 of the total, the sub-loop output is stable; otherwise, the branch is unstable, and the output of the sub-loop with the minimum noise intensity is selected as the feedback of the sub-loop; based on this criterion, the tracking fusion algorithm selects the appropriate doppler shift measurement to feed back to the loop to generate the desired local carrier. The specific process is as follows:
if the branch output is stable, either
Figure BDA0001378816270000085
The feedback is then:
Figure BDA0001378816270000086
if the branch output is unstable, either
Figure BDA0001378816270000087
The feedback is then:
Figure BDA0001378816270000088
γii≥γmmi, m ≠ N, and i, m ≠ N
In step C, the redundant data is integrated by an output fusion algorithm to obtain a final output estimate, and the specific process is as follows:
and C: and carrying out weighted average on the redundant data, wherein the weighting principle is as follows: presence weight coefficient vector wTSuch that the following equation is minimized:
Jw＝wTQ1w-Q2w
wherein
Figure BDA0001378816270000089
An NxN order covariance matrix representing two different sub-loop measurements;
Figure BDA00013788162700000810
representing a measurement uncertainty vector; q. q.s1,nmAnd q is2,nCan be calculated by the following formula:
q1,nm＝E[εn(k)εm(k)]
Figure BDA00013788162700000811
the final output results are:
Figure BDA00013788162700000812
wherein,
Figure BDA00013788162700000813
denotes the measurement vector, where w ═ w1...wN]TIs a weight coefficient vector, w is more than or equal to 0iLess than or equal to 1 and
Figure BDA0001378816270000091
the above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, but any modifications or equivalent variations made according to the technical spirit of the present invention are within the scope of the present invention as claimed.

Claims (2)

1. A multi-PLL carrier tracking loop that effectively mitigates ionospheric flicker effects, comprising the steps of:
step A: by proximity deltanmThe size determines the correlation between different sub-loops, and a threshold value delta is set0In step A, delta is determined by distinguishing and selecting loosely coupled sub-loops with different performances, and performing correlation operation on output errors and variances of the errors of the sub-loops to obtain compatibilitynmAnd gammanm(k) The specific process of the calculation formula and the selection basis of the sub-loop thereof is as follows:
step A-1: selecting loosely coupled sub-loops with different properties, using closeness deltanmTo describe the correlation between different sub-loops:
Figure FDA0002371834910000011
wherein upsilon isn(k) To be the output error of the sub-loop n,
Figure FDA0002371834910000012
setting a threshold delta for the variance of the sub-loop n-errors00.5, selecting the closeness degree deltanmLess than threshold delta0The loosely coupled sub-loop of (a);
step A-2: subtracting the Doppler frequency shift of the two sub-loops in the kth sampling period to obtain an error term epsilonnm(k) The specific process is as follows:
εnm(k)＝ωD,n(k)-ωD,m(k)＝υn(k)-υm(k),(m＝1,...,Nandm≠n)；
then the compatibility can be expressed as:
Figure FDA0002371834910000013
wherein, γnm(k) Has a value range of [0,1 ]]，γnm(k) Greater than 0 indicates that the sub-loops n and m are compatible with each other, γ, in the kth sampling periodnm(k) A value equal to 0 indicates that the sub-loops n and m oppose each other, and when the sub-loops n oppose the total number of the 2/3, the output result is unreliable to judge the validity of the output of the sub-loop;
and B: taking the integration time of the current sub-loop as a standard, sampling the integration time of other sub-loops upwards or downwards to determine the output with uniform integration time, judging the stability of the output of the sub-loop according to the compatibility, and estimating the feedback of the sub-loop according to the stability principle;
in the step B, the output of the sub-loop is determined through a tracking fusion algorithm, the integral time of each sub-loop is unified, and then the feedback result is determined through a stability principle, and the specific process is as follows:
step B-1: preprocessing to unify integration time with integration time T of the current sub-loopcoh,nAs a reference standard, for example, the integration time T of the other sub-loops is calculated by the following algorithmcoh,mConversion to Tcoh,nThe specific process comprises the following steps:
if Tcoh,m＞Tcoh,nThen, upsampling:
ωD,m(kn+l)＝ωD,m(km)；
wherein k isn＝Mkm1, M-1 and
Figure FDA0002371834910000021
rounding M;
if Tcoh,m＜Tcoh,nThen, down-sampling:
Figure FDA0002371834910000022
wherein,
Figure FDA0002371834910000023
rounding M;
step B-2: calculating the compatibility of the sub-loop according to gammanm(k) The number greater than 0 determines the stability of the sub-loop according to the following:
if it is
Figure FDA0002371834910000024
Greater than 1/3 of the total number, the output of the sub-loop is stable and its feedback is:
Figure FDA0002371834910000025
if it is
Figure FDA0002371834910000026
Is less than 1/3 of the total number, the output of the sub-loop is unstable, and the sub-loop output with the least noise strength is selected as the feedback of the sub-loop:
Figure FDA0002371834910000027
wherein gamma isii(k) Indicated is the compatibility when n ═ m, which reflects the measured noise strength of the sub-loop i;
and C: and selecting a weight coefficient according to the principle of minimum error to perform weighted average on the feedback of each sub-loop, and integrating redundant measurement data to obtain a continuous and accurate final output value.
2. The multi-PLL carrier tracking loop capable of effectively reducing ionospheric flicker effect as claimed in claim 1, wherein in step C, redundant data is integrated by an output fusion algorithm to obtain a final output estimate, the specific process is as follows:
and C: and carrying out weighted average on the redundant data, wherein the weighting principle is as follows: presence weight coefficient vector wTSuch that the following equation is minimized: j. the design is a squarew＝wTQ1w-Q2w；
Wherein Q1＝[q1,nm]N×NAn NxN order covariance matrix representing two different sub-loop measurements; q2＝[q2,1...q2,N]Representing the measured uncertainty vector, q1,nmAnd q is2,nCan be calculated by the following formula:
q1,nm＝E[εn(k)εm(k)]；
Figure FDA0002371834910000031
the final output results are:
Figure FDA0002371834910000032
wherein,
Figure FDA0002371834910000033
representing the measurement vector.
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