CN109633698B - Indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering - Google Patents

Indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering Download PDF

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CN109633698B
CN109633698B CN201811617458.6A CN201811617458A CN109633698B CN 109633698 B CN109633698 B CN 109633698B CN 201811617458 A CN201811617458 A CN 201811617458A CN 109633698 B CN109633698 B CN 109633698B
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pseudolite
carrier
multipath
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CN109633698A (en
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王庆
杨高朝
吴向阳
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Southeast University
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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
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/22—Multipath-related issues
    • 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
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/35—Constructional details or hardware or software details of the signal processing chain
    • G01S19/37—Hardware or software details of the signal processing chain
    • 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
    • G01S19/40—Correcting position, velocity or attitude

Abstract

The invention discloses an indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering, which comprises the following steps: the method comprises the following steps that a pseudo satellite receiver receives a synthetic signal which is sent by a pseudo satellite and formed by a direct signal and a multipath signal, and the high-frequency signal in the synthetic signal is subjected to frequency reduction to obtain an intermediate-frequency synthetic signal; dividing the pseudo satellite signal into two paths of signals I and Q, tracking a received pseudo satellite carrier synthesized signal by adjusting the symbol width among early, late and punctual signals generated by a local numerical control oscillator, and tracking and measuring a pseudo range, a carrier and a carrier-to-noise ratio from the pseudo satellite to a receiver by a delay locked loop; establishing a single difference observation equation and a double difference observation equation of the linearized pseudolite; and acquiring an observation error equation and a state prediction equation based on an adaptive robust filtering principle, calculating to obtain a state vector post-test covariance matrix and an observation equivalent matrix, adjusting an adaptive factor and an observation equivalent weight matrix according to a carrier-to-noise ratio, acquiring to obtain different filtering solutions and outputting the position of the pseudo satellite receiver. The invention can effectively reduce the influence of multipath errors on the positioning precision of the pseudo satellite, and the influence of the multipath errors on the pseudo range positioning is below a meter level.

Description

Indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering
Technical Field
The invention relates to an indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering, and belongs to the technical field of satellite navigation positioning.
Background
In recent years, the pseudolite technology has been widely studied at home and abroad, and similar to GNSS satellites, pseudolites are positioned by using time parameters of signals, and as the application prospect of the pseudolites is well known, more students can carry out deep research on the pseudolites. In recent twenty years, people use pseudolites in many fields, such as deformation detection of dams and bridges, high-speed train tracking, mars detection, positioning in underground tunnels and the like, and recently, researchers propose that pseudolites are used for indoor positioning to realize high-precision indoor positioning targets, so that the technology has infinite potential.
Many new problems arise in pseudolite applications, such as multipath effects, near-far effects, and time synchronization. The multipath effect is caused by multipath propagation of satellite signals, that is, the receiver antenna receives not only direct wave signals but also one or more reflected wave signals of various surrounding media during reception. These signals interfere with the directly propagated signals, so that the observed values deviate from the true values, and the resulting interference delay effect is called multipath effect. As with GNSS signals, GNSS pseudolite signals inevitably exhibit multipath effects during propagation and are more difficult to cancel.
For GNSS satellites, the multipath components of the transmission are generally small. Since the unit vectors from the GNSS reference station and the receiver to a particular satellite are substantially the same, the multipath effects can be directly eliminated using differential techniques. Since the position arrangement, signal strength, working environment, etc. of the pseudolite are different from those of the GNSS, it is stronger, more complex and more difficult to eliminate than the multipath error of the GNSS signal, which is also an important factor considered in data processing. Through the research and test of scholars at home and abroad, the multipath effect has the following characteristics:
1) GNSS multipath signals typically result from multipath interference signals from an emitting surface below the antenna, while pseudolite signals typically result from an emitting signal from an emitting surface above the antenna, and even from the pseudolite itself. Thus, the receiver antenna may shield some of the multipath interference for GNSS signals, but generally cannot shield the multipath interference for pseudolite signals.
2) The receiver elevation angle to the pseudolite is small compared to GNSS, and thus the multipath effects from the pseudolite are much more severe than GNSS signals. Low elevation angles (10 ° or 15 °) in GNSS measurements are typically rejected to reduce multipath effects and the more severe tropospheric delay problems that pseudolites cannot handle.
3) Pseudolites are typically fixed in a known position (which may be accurately determined in advance), and thus if the receiver is also stationary, its multipath effects may form an offset that is not easily eliminated. Unlike GNSS satellite signals, multipath effects can generally be averaged out and reduced to some degree. Pseudolite signal multipath errors generally cannot be mitigated by smoothing.
4) Pseudolites are typically terrestrial and GNSS satellites are in space, so that multipath effects from GNSS propagated signals are much smaller than from pseudolites. Since far-spaced space means that any multipath effects will produce slowly varying offsets in the transmitted signal, these multipath signals are highly correlated in the spatial viewpoint.
5) The GNSS multipath error can be generally used as noise smoothing processing, the multipath of a pseudo code measured by the HuangDing method and the like is about 10M at most, and the multipath error of a carrier phase is about 1/4 wavelength at most, namely about 5 CM. The pseudolite multipath is far larger than the value, the maximum influence value is not well counted at present, and the carrier phase whole-cycle ambiguity generally cannot be fixed without a good reason.
The amount of error due to multipath effects is determined by the characteristics of the correlators and the tracking lock loop in the receiver. Currently, carrier phase multipath is an important error source that restricts high-precision GNSS and pseudolite measurement or deformation monitoring. Multipath effects affect not only the carrier observations, but also the carrier-to-noise ratio SNR, and the observations are more sensitive to carrier phase multipath.
The existing methods for solving the multipath error can be roughly classified into three types: one is to adopt some antenna techniques which can inhibit multipath, such as choke coils, a path-inhibiting plate, multi-antenna positioning and the like; secondly, the improvement of the performance of a carrier tracking loop and a delay locking loop in the receiver and the adjustment of the loop bandwidth, such as narrow correlation technique, leading edge detection technique and the like; and thirdly, a pseudo range and position domain signal post-processing method, wherein a semi-parameter model method, a numerical analysis method by utilizing wavelets and a spectrum analysis method based on a carrier-to-noise ratio are typical in the pseudo range and position domain signal post-processing method. The solutions of these methods are complex, and the key steps are difficult to master. The first two are from a hardware design perspective and the third is from a data post-processing perspective.
Disclosure of Invention
The invention aims to solve the technical problems that pseudolite multipath seriously affects the positioning precision of a receiver, the receiver cannot be tracked and unlocked usually when the surrounding environment is complex, the ambiguity of the whole cycle of the carrier phase cannot be fixed, pseudo range or floating solution can be used for resolving during positioning, and the advantages of the pseudolite cannot be exerted.
The invention specifically adopts the following technical scheme to solve the technical problems:
an indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering comprises the following steps:
the pseudo-satellite receiver receives a synthetic signal which is sent by a satellite and formed by a direct signal and a multipath signal, and down-converts a high-frequency signal in the synthetic signal to obtain an intermediate-frequency synthetic signal;
dividing an intermediate frequency synthetic signal obtained by a pseudo satellite receiver into an I signal and a Q signal, respectively tracking by adopting alignment signals generated by local carriers, and carrying out correlation operation to obtain an alignment correlation value of an in-phase channel; measuring the time delay estimation of the intermediate frequency synthetic signal according to the alignment correlation value of the in-phase channel and the carrier wave generated by the local numerical control oscillator, and tracking and measuring the pseudo range, the carrier wave and the carrier-to-noise ratio from the pseudolite to the pseudolite receiver by a time delay locking ring;
establishing a linearized pseudolite double-difference observation equation according to the measured pseudo range, carrier and carrier-to-noise ratio from the pseudolite to the pseudolite receiver, and weighting each observation value in the pseudolite double-difference observation equation according to the carrier-to-noise ratio;
forming an observation error equation and a state prediction equation based on a self-adaptive robust filtering principle according to a double-difference observation equation of the pseudolite after weighting of an observed value; and adjusting the carrier-to-noise ratio of the observed value in the observation error equation to obtain an observation equivalent matrix, obtaining different filtering solutions according to the adaptive factor, the observation equivalent weight matrix and the state prediction equation, and solving and outputting the position of the pseudo satellite receiver.
Further, as a preferred technical solution of the present invention, the intermediate frequency synthesized signal obtained by the pseudolite receiver in the method specifically includes:
Figure BDA0001924594610000031
wherein s (t) is the intermediate frequency synthesis signal after frequency reduction; m is the number of multipath signals;αiis the signal amplitude fading coefficient; a is the carrier amplitude; d (t) is navigation data information; c (t- τ)i) Is t-tauiPseudolite spread spectrum pseudo-random code of the moment; w is a0Intermediate frequency of the pseudolite direct signal; phi is ai(t) is the phase of the ith signal at time t; tau isiAnd estimating the time delay of the non-direct signal of the pseudolite.
Further, as a preferred technical solution of the present invention, the alignment signal generated by the local carrier in the method specifically includes:
Figure BDA0001924594610000032
Figure BDA0001924594610000033
wherein p isI(t) and pQ(t) are local mutually orthogonal alignment signals generated by the pseudolite receiver, respectively, and t is time;
Figure BDA0001924594610000034
is composed of
Figure BDA0001924594610000035
Pseudolite spread spectrum pseudorandom code of time of day, wherein
Figure BDA0001924594610000036
Estimating the time delay of a pseudo satellite direct signal; w is a0Intermediate frequency of the pseudolite direct signal;
Figure BDA0001924594610000037
carrier phase estimation for the pseudolite direct signal.
Further, as a preferred technical solution of the present invention, the alignment correlation value IP of the in-phase channel obtained by performing correlation operation in the method specifically includes:
Figure BDA0001924594610000041
wherein M is the number of multipath signals; alpha is alphaiIs the signal amplitude fading coefficient; r (tau) is the autocorrelation function of the electromagnetic wave spreading code;
Figure BDA0001924594610000042
estimating the time delay of a pseudo satellite direct signal; tau isiEstimating the time delay of the non-direct signal of the pseudolite; phi is aiCarrier phase estimation for the ith pseudolite non-direct signal;
Figure BDA0001924594610000043
carrier phase estimation for the pseudolite direct signal.
Further, as a preferred technical solution of the present invention, the method establishes a linearized pseudolite single-difference and double-difference combined observation equation, specifically:
Figure BDA0001924594610000044
Figure BDA0001924594610000045
wherein epsilonkObserving noise for the pseudolite; a. thekIs an observation equation coefficient matrix; l iskIs an observation vector;
Figure BDA0001924594610000046
and
Figure BDA0001924594610000047
are each tkAnd tk-1A state estimation vector at a time; phik,k-1Is a state transition matrix; deltakIs state noise.
By adopting the technical scheme, the invention can produce the following technical effects:
the most important error in pseudo satellite positioning is the influence of multipath delay, the method of the invention researches the weakening of multipath error from baseband signal processing and later data fusion, the baseband signal processing adopts the narrow correlation difference technology to adjust the code element width and the tracking loop bandwidth, the processed signal is output to a data resolving module, and the adaptive anti-difference filtering technology is adopted to reduce the weight of multipath observed value to weaken the influence of multipath error on the pseudo satellite positioning precision; the invention can reflect the signal quality based on the signal carrier-to-noise ratio SNR of the signal, and when a multipath effect occurs, the SNR value of the satellite observation value in the period is correspondingly reduced, thereby providing a method for weakening the multipath effect according to the change of the SNR value.
Therefore, the method can effectively reduce the influence of the multipath error on the positioning precision of the pseudo satellite, and the influence of the multipath error on the pseudo range positioning is below a meter level; the effect on carrier phase positioning is below centimeter level.
Drawings
Fig. 1 is a schematic structural diagram of a pseudolite indoor positioning system according to the present invention.
Fig. 2 is a schematic diagram illustrating the principle of the indoor pseudolite anti-multipath method based on narrow correlation and robust adaptive filtering according to the present invention.
Detailed Description
The following describes embodiments of the present invention with reference to the drawings.
The invention designs an indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering, and a system applied by the method is shown in figure 1 and comprises hardware such as a pseudo satellite signal transmitter, a radio receiver and the like, and software such as a Software Defined Radio (SDR) receiver and the like.
As shown in fig. 2, the method for resisting multipath for an indoor pseudolite based on narrow correlation and robust adaptive filtering of the present invention specifically includes the following steps:
and step 1, performing a narrow correlation delay tracking loop.
Step 11, the pseudolite receiver receives a composite signal formed by a direct signal and a multipath signal sent by a satellite, and down-converts a high-frequency signal in the composite signal to obtain an intermediate-frequency composite signal s (t), which can be represented as:
Figure BDA0001924594610000051
wherein, i-0 represents the pseudo satellite direct signal, the others are M multipath signals, and M is the number of the multipath signals; alpha is alphaiIs the signal amplitude fading coefficient; a is the carrier amplitude; d (t) is navigation data information; c (t- τ)i) Is t-tauiPseudolite spread spectrum pseudo-random code of the moment; w is a0For the intermediate frequency of the pseudolite direct signal, the present embodiment assumes that the direct signal and the multipath signal have the same frequency; phi is ai(t) is the phase of the ith signal at time t; tau isiAnd estimating the time delay of the non-direct signal of the pseudolite.
The multipath signal generally has a certain delay and has an attenuation amplitude relative to a direct-view signal (LOS), when the multipath delay is less than 2 code elements wide, the multipath signal has a certain correlation with the direct-view signal, otherwise, the influence of the multipath signal can be ignored.
Step 12, dividing the intermediate frequency synthetic signal obtained by the pseudo satellite receiver into two paths of signals I and Q, respectively tracking by adopting alignment signals generated by local carriers, and carrying out correlation operation to obtain an alignment correlation value of an in-phase channel; measuring the time delay estimation of the intermediate frequency synthetic signal according to the alignment correlation value of the in-phase channel and the tracking carrier generated by the local numerically-controlled oscillator, and tracking and measuring the pseudo range, the carrier and the carrier-to-noise ratio from the pseudolite to the pseudolite receiver by the time delay locking ring; the method comprises the following specific steps:
assuming that the local carrier correctly tracks the frequency of the received signal, the locally generated alignment signal can be expressed as:
Figure BDA0001924594610000052
Figure BDA0001924594610000053
wherein p isI(t) and pQ(t) are respectively pseudo guardsLocal mutually orthogonal alignment signals generated by a satellite receiver, wherein t is time;
Figure BDA0001924594610000054
is composed of
Figure BDA0001924594610000055
Pseudolite spread spectrum pseudorandom code of time of day, wherein
Figure BDA0001924594610000056
Estimating the time delay of a pseudo satellite direct signal; w is a0Intermediate frequency of the pseudolite direct signal;
Figure BDA0001924594610000061
carrier phase estimation for the pseudolite direct signal.
The alignment correlation value of the in-phase channel obtained by correlating the received signal with the local signal can be expressed as:
Figure BDA0001924594610000062
in the formula:
Figure BDA0001924594610000063
for the estimation of the time delay of the pseudolite direct signal,
Figure BDA0001924594610000064
carrier phase estimation for pseudolite direct signal, phiiCarrier phase estimation for the ith pseudolite non-direct signal; r (tau) is an autocorrelation function of the electromagnetic wave spreading code, and the expression is as follows:
Figure BDA0001924594610000065
wherein, TcIs the code element width of the pseudolite electromagnetic wave C/A code.
The general GNSS receiver utilizes three correlators of alignment Prompt, advance Early and lag LateAcquiring and tracking pseudo-random code by correlation technique, and estimating time delay of measured pseudo-satellite direct signal to be tau0Then tracking τ by the delay locked loop0And then measuring the pseudoranges of the pseudolites to the pseudolite receiver.
The carrier phase tracking loop of the receiver is a phase-locked loop (PLL) and a delay tracking loop (DLL). I and Q are in-phase and anti-phase energy signals, respectively, sin and cos signals are carrier replica signals generated by a carrier phase tracking loop that takes into account doppler shifted carriers, E, L, P are early, late and on-time signals generated by a local numerically controlled oscillator, respectively, which is reduced by a symbol width of between E, L, P according to the invention requirements. The received electromagnetic wave signal is multiplied by a locally generated carrier wave through a PLL according to the formula (1) to obtain a baseband signal, the baseband signal is sent to an early-late correlator after a circuit is stabilized, the early-late correlator carries out code correlation calculation on the baseband signal after fading in a delay tracking loop, namely, demodulated signals are respectively multiplied by E, L, P which is locally generated, when the correlation value of a pseudo satellite signal and a time-of-arrival code is maximum, the time of the received signal in space propagation is obtained, and further, the pseudo range, the navigation message and the carrier wave are demodulated, namely, output observed values are realized. The correlation outputs are compared by a phase detector to control the delay time or code element of the current code to match the pseudo random code of the next input signal. The bandwidth selection for the receiver loop needs to take into account two factors: when the interference of noise occurs, the loop bandwidth needs to be narrowed so as to reduce the influence of noise and improve the carrier-to-noise ratio; the loop needs to be widened when highly dynamic by the carrier in order to be able to reduce the effect of doppler shift on the acquired signal. The invention can adjust the bandwidth of the loop in real time according to the carrier-to-noise ratio output in the loop. The design of the early-late correlator, the phase detector and the loop bandwidth plays an important role in eliminating multipath errors and tracking and capturing signals.
And 2, establishing a pseudo satellite combined observation model. Establishing a linearized pseudolite double-difference observation equation according to the pseudo-range, carrier wave, carrier-to-noise ratio and other numerical values from the satellite to the pseudolite receiver measured in the step 1, and weighting each observation value in the pseudolite double-difference observation equation according to the carrier-to-noise ratio; the method comprises the following specific steps:
assuming that k pseudolites are synchronously observed by the ith epoch, the two observation stations T1 and T2, the distance between the two observation stations is less than 1km, and the reference star selected by the epoch is r, the linearized pseudolites single-difference and double-difference combined observation equations are respectively shown in the formula (8) and the formula (9).
Figure BDA0001924594610000071
Wherein
Figure BDA0001924594610000072
Is the observed phase value;
Figure BDA0001924594610000073
is the pseudolite receiver to pseudolite range; λ is the wavelength of the pseudolite carrier; t is tiFor pseudolite receiver clock error, tjClock error of pseudolite; MP (moving Picture experts group)i jIs a pseudolite carrier multipath error;
Figure BDA0001924594610000074
pseudolite tropospheric errors;
Figure BDA0001924594610000075
is the receiver noise.
Figure BDA0001924594610000076
SD is the equation of single difference between stations,
Figure BDA0001924594610000077
single difference values for 1 and 2 survey station phase observations;
Figure BDA0001924594610000078
the single difference of the measuring station distance is obtained;
Figure BDA0001924594610000079
is the single difference ambiguity; δ t1,2The clock error single difference of the receiver of the station is measured;
Figure BDA00019245946100000710
is a multipath single difference;
Figure BDA00019245946100000711
is tropospheric homodyne;
Figure BDA00019245946100000712
is single difference noise.
Figure BDA00019245946100000713
Wherein DD is the equation of double differences between stations,
Figure BDA00019245946100000714
respectively, the double-difference phase observed values of the mth pseudolite,
Figure BDA00019245946100000715
the distance double differences of the measuring stations are obtained;
Figure BDA00019245946100000716
is double-difference ambiguity;
Figure BDA00019245946100000717
the single difference tropospheric delay for the jth pseudolite,
Figure BDA00019245946100000718
double difference multipath error of the mth pseudolite;
Figure BDA00019245946100000719
is the tropospheric double difference;
Figure BDA00019245946100000720
is double difference noise. (the equations above are for the reference station 1, rover 2, and reference satellite γ.)
After Taylor formula expansion, an error equation can be formed according to a pseudolite double-difference observation equation as follows:
Figure BDA00019245946100000721
wherein the content of the first and second substances,
Figure BDA00019245946100000722
Xr＝[ΔXr,ΔYr,ΔZr]Tin the form of a matrix of position vectors,
Figure BDA0001924594610000081
for double-difference ambiguities, L is a constant matrix,
Figure BDA0001924594610000082
the rover's distance to the ith satellite,
Figure BDA0001924594610000083
as initial coordinates of the rover, xi、yi、ziIs the coordinates of the ith satellite and,
Figure BDA0001924594610000084
to observe the noise.
At this time, an error equation can be established for the double-difference phase observed value according to the least square principle, and then the base line vector is determined by adjustment. Generally, for small regions (usually region radii)<10km) short time (10-30min) static positioning, tropospheric delay errors can be considered due to the relatively fixed pseudolite propagation signals and the short baseline
Figure BDA0001924594610000085
Is 0, do not take into account multipath effects
Figure BDA0001924594610000086
Subject to a normal distribution that is expected not to be 0. However, in practical observation, the signal may be propagatedOccasional abrupt changes may occur that cause multipath effects not to fully obey the distribution described above. Therefore, in order to separate the phase observation values affected by the abnormal values during the data processing, it can be considered that the phase observation values are in [ c, -c]The residual error main body of the internal double-difference observation equation follows normal distribution, and a small part of double-difference observation values containing interference terms are in the range of < - ∞andc]And [ c, + ∞ -]Inner (c is the error in doubling the a priori unit weights) follows the synthesis of normal distributions and other distributions.
Given that the weights of observations on the Ll and L2 carriers are determined inversely proportional to their mean square error, the more severe the multipath, the smaller the carrier-to-noise ratio observations, and the larger the mean square error of the observations, the approximation equation:
Figure BDA0001924594610000087
representing the mean square error of the observations on the Ll carrier, where B is the noise bandwidth of the receiver phase-locked loop, c/n0Is the carrier to noise ratio strength. The above formula shows that: the magnitude of the variance of the pseudolite observations is determined by the carrier-to-noise ratio SNR of the epoch observations and the bandwidth B in the pseudolite receiver. Mean square error due to pseudolite observations and
Figure BDA0001924594610000088
and the linear relation is formed, so that the mean square error ratio, namely the weight, among all epochs of the same B-value satellite observation value is kept unchanged. Therefore, the weight relation among the observation values of all epochs of the same satellite is not influenced by the B value, a weight can be fixed for one observation value according to the carrier-to-noise ratio, and a smaller weight is assigned to the observation value with the smaller carrier-to-noise ratio, so that the influence on the positioning result is weakened.
And 3, self-adaptive robust fusion. Forming an observation error equation and a state prediction equation based on a self-adaptive robust filtering principle according to a double-difference observation equation of the pseudolite after weighting of an observed value; and adjusting the carrier-to-noise ratio of the observed value in the observation error equation to obtain an observation equivalent matrix, obtaining different filtering solutions according to the adaptive factor, the observation equivalent weight matrix and the state prediction equation, and solving and outputting the position of the pseudo satellite receiver. The method comprises the following specific steps:
the double difference between the carrier and the pseudorange is used as the observation model, as shown in the above equation (2). The filtering random model of the invention adopts a variance expansion model, namely, multipath errors are taken as a part of the random model, observed values of the multipath errors are taken as the variance of the observed values to change, but the mathematical expectation is unchanged, for the convenience of satellite change, a coordinate vector and a single-difference ambiguity are taken as state vectors to be solved, a double-difference observation model is formed by assuming that 7 pseudo satellites are observed and a star 2 is taken as a reference satellite, and an observation error equation and a state prediction equation are obtained by a formula (10):
Figure BDA0001924594610000091
Figure BDA0001924594610000092
in the formula (I), the compound is shown in the specification,
Figure BDA0001924594610000093
and
Figure BDA0001924594610000094
are each tkAnd tk-1The state estimate vector for the time of day,
Figure BDA0001924594610000095
Figure BDA0001924594610000096
obtaining pseudo range and carrier observation double difference values for demodulation;
Figure BDA0001924594610000097
Φk,k-1is an identity matrix; epsilonkObserving noise for the pseudolite; l iskIs an observation vector; phik,k-1Is a state transition matrix; deltakIs state noise;
Akthe matrix is a double difference coefficient matrix and is obtained by the formula (10), and the constructed adaptive robust filtering principle is as follows:
Figure BDA0001924594610000098
in the formula (I), the compound is shown in the specification,
Figure BDA0001924594610000099
for the observation vector LkThe covariance matrix of (a) is determined,
Figure BDA00019245946100000910
Skfor the demodulated measured carrier-to-noise ratio, alphakAs an adaptation factor, Xk|k-1For a one-step prediction matrix, Pk|k-1The covariance matrix is predicted for the prediction state vector in one step. Obtaining the following result after solving an extreme value according to the conditional least square:
Figure BDA00019245946100000911
in the formula (I), the compound is shown in the specification,
Figure BDA00019245946100000912
for the filtered pseudolite receiver position, the above equation can be equivalently written according to the matrix inversion formula:
Figure BDA00019245946100000913
wherein
Figure BDA0001924594610000101
Is an equivalent gain matrix, specifically:
Figure BDA0001924594610000102
wherein the content of the first and second substances,
Figure BDA0001924594610000103
the state vector post-test covariance matrix is:
Figure BDA0001924594610000104
with adaptive factor alphakAnd observing the equivalence weight matrix
Figure BDA0001924594610000105
Different, different filter solutions can be obtained, and equivalent matrixes can be observed
Figure BDA0001924594610000106
The carrier-to-noise ratio can be adjusted based on the observed values, the principle of which is shown in fig. 2.
After baseband signals and robust adaptive filtering processing, the position of the receiver is output, and through preliminary verification, the reliability and the positioning precision of data are improved to a great extent, and the indoor positioning result can be improved by one order of magnitude.
In order to verify that the method of the present invention can reduce the influence of multipath data on the positioning accuracy, a verification example is provided for description.
Verification examples 1,
In the verification example, a pseudolite project of the medium-power station 54 is used as a support, and a pseudolite indoor positioning system built in the pseudolite indoor positioning system is used, so that research is performed around the main difficult multipath effect of indoor positioning as shown in fig. 1. According to the built pseudolite experimental environment, a software receiver is used for receiving pseudolite signals, and the influence of multi-collar effect on positioning is weakened through adjusting loop bandwidth in baseband signal processing and performing robust adaptive fusion in data post-processing. The process of the verification example comprises the following steps:
1. in the baseband signal processing of the software receiver, the narrow correlation difference technology of the multi-correlator is utilized for signal tracking, the loop bandwidth is dynamically adjusted according to the phase difference in the phase discriminator, and experiments prove that the influence of multipath errors on the observation precision can be effectively weakened.
2. The signals processed by the baseband signals are decoded and then sent to a post-processing link for robust adaptive filtering fusion, the weight of an observed value is adjusted according to the carrier-to-noise ratio in the observed data, finally, different filtering solutions are obtained through an adaptive factor, an observation equivalent weight matrix and a state prediction equation, the position of a pseudo satellite receiver is obtained and output, and the weight of the observed value with large multipath error is reduced during resolving so as to weaken the influence of the multipath data on the positioning precision.
In conclusion, the method for weakening the multipath effect according to the change of the SNR value is provided, so that the influence of the multipath error on the positioning precision of the pseudo-satellite can be effectively reduced, and the influence of the multipath error on the pseudo-range positioning is below a meter level; the effect on carrier phase positioning is below centimeter level.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.

Claims (5)

1. An indoor pseudo satellite anti-multipath method based on narrow correlation and robust adaptive filtering is characterized by comprising the following steps:
the pseudo-satellite receiver receives a synthetic signal which is sent by a satellite and formed by a direct signal and a multipath signal, and down-converts a high-frequency signal in the synthetic signal to obtain an intermediate-frequency synthetic signal;
dividing an intermediate frequency synthetic signal obtained by a pseudo satellite receiver into an I signal and a Q signal, respectively tracking by adopting alignment signals generated by local carriers, and carrying out correlation operation to obtain an alignment correlation value of an in-phase channel; measuring the time delay estimation of the intermediate frequency synthetic signal according to the alignment correlation value of the in-phase channel and a tracking signal generated by a local numerically-controlled oscillator, and tracking and measuring the pseudo range, carrier and carrier-to-noise ratio from the pseudolite to a pseudolite receiver by a time delay locking ring;
establishing a linearized pseudolite double-difference observation equation according to the measured pseudo range, carrier and carrier-to-noise ratio from the pseudolite to the pseudolite receiver, and weighting each observation value in the pseudolite double-difference observation equation according to the carrier-to-noise ratio;
forming an observation error equation and a state prediction equation based on a self-adaptive robust filtering principle according to a double-difference observation equation of the pseudolite after weighting of an observed value; and adjusting the carrier-to-noise ratio of the observed value in the observation error equation to obtain an observation equivalent matrix, obtaining different filtering solutions according to the adaptive factor, the observation equivalent weight matrix and the state prediction equation, and solving and outputting the position of the pseudo satellite receiver.
2. The narrow correlation and robust adaptive filtering based indoor pseudolite multipath mitigation method of claim 1, wherein the intermediate frequency composite signal obtained by the pseudolite receiver in the method is specifically:
Figure FDA0001924594600000011
wherein s (t) is the intermediate frequency synthesis signal after frequency reduction; m is the number of multipath signals; alpha is alphaiIs the signal amplitude fading coefficient; a is the carrier amplitude; d (t) is navigation data information; c (t- τ)i) Is t-tauiPseudolite spread spectrum pseudo-random code of the moment; w is a0Intermediate frequency of the pseudolite direct signal; phi is ai(t) is the phase of the ith signal at time t; tau isiAnd estimating the time delay of the non-direct signal of the pseudolite.
3. The narrow correlation and robust adaptive filtering based indoor pseudo satellite multipath mitigation method of claim 1, wherein the alignment signal generated by the local carrier in the method is specifically:
Figure FDA0001924594600000012
Figure FDA0001924594600000013
wherein p isI(t) and pQ(t) are local mutually orthogonal alignment signals generated by the pseudolite receiver, respectively, and t is time;
Figure FDA0001924594600000021
is composed of
Figure FDA0001924594600000022
Pseudolite spread spectrum pseudorandom code of time of day, wherein
Figure FDA0001924594600000023
Estimating the time delay of a pseudo satellite direct signal; w is a0Intermediate frequency of the pseudolite direct signal;
Figure FDA0001924594600000024
carrier phase estimation for the pseudolite direct signal.
4. The narrow correlation and robust adaptive filtering-based indoor pseudolite anti-multipath method according to claim 1, wherein the alignment correlation value IP of the in-phase channel obtained by performing correlation operation in the method specifically comprises:
Figure FDA0001924594600000025
wherein M is the number of multipath signals; alpha is alphaiIs the signal amplitude fading coefficient; r (tau) is the autocorrelation function of the electromagnetic wave spreading code;
Figure FDA0001924594600000026
estimating the time delay of a pseudo satellite direct signal; tau isiEstimating the time delay of the non-direct signal of the pseudolite; phi is aiCarrier phase estimation for the ith pseudolite non-direct signal;
Figure FDA0001924594600000027
carrier phase estimation for the pseudolite direct signal.
5. The narrow correlation and robust adaptive filtering based indoor pseudo satellite multipath mitigation method according to claim 1, wherein robust adaptive filtering is performed on a pseudo satellite double-difference observation equation according to the method, and a formula is adopted:
Figure FDA0001924594600000028
Figure FDA0001924594600000029
wherein epsilonkObserving noise for the pseudolite; a. thekIs an observation equation coefficient matrix; l iskIs an observation vector;
Figure FDA00019245946000000210
and
Figure FDA00019245946000000211
are each tkAnd tk-1A state estimation vector at a time; phik,k-1Is a state transition matrix; deltakIs state noise.
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