CN101825717A - Carrier smoothing code pseudorange technology-based dynamic attitude positioning method - Google Patents

Abstract

The invention discloses a carrier smoothing code pseudorange technology-based dynamic attitude positioning algorithm method, which comprises the following steps of: (1) detecting whether cycle slip occurs in the current epoch by using a three-difference method, if so, using the code observation of the current epoch, otherwise, acquiring the smoothed code observation by using Hatch filtering and recording the smoothing window length k; (2) solving the floating solution of the integer ambiguity and the variance-covariance matrix of the floating solution by utilizing the code observation and the code observation of the current epoch; (3) taking the floating solution of the integer ambiguity and the variance-covariance matrix of the floating solution as initial parameters, substituting the initial parameters into an LAMBDA algorithm for solving the fixed solution of the ambiguity, and acquiring former N ambiguity candidate values; and (4) performing the ambiguity test on the former N ambiguity candidate values in turn, until the ambiguity candidate solution meeting the constraint condition is found, and solving the obtained attitude angle. The carrier smoothing code pseudorange technology-based dynamic attitude positioning algorithm method does not have the problem of initialization time, can be effectively used for real-time dynamic attitude measurement, and can self-adaptively regulate the smoothing window length and the ambiguity candidate solution space aiming at the occurrence of the cycle slip. Therefore, the success rate and the overall efficiency of the algorithm are improved.

Description

A kind of dynamic method for determining posture based on carrier smoothing code pseudorange technology

Technical field

The present invention relates to a kind of dynamic method for determining posture, belong to satellite orientation and decide the appearance technical field based on carrier smoothing code pseudorange technology.

Background technology

Attitude measurement generally is applied on satellite, spacecraft, manned machine, unmanned plane, boats and ships, the contour dynamic carrier of automobile, and these carriers require attitude measurement systems to have precision height, characteristics such as real-time, easy for installation.The attitude algorithm system has important strategic meaning and using value for national defence and aerospace field during high-precision real.

GPS (GPS) has global, round-the-clock and continuous accurate three-dimensional localization ability.In year surplus in the of nearly ten, GPS has been widely applied to various fields.The GPS precision positioning comprises two general orientation, i.e. single-point location and the relative positioning between 2.Attitude algorithm is the relative geometry position relation between 2 in the space of research in essence, and therefore carrying out the high precision relative positioning by gps signal can finish attitude algorithm.

Utilize gps signal to carry out attitude measurement and resolve attitude than traditional inertia device and have advantages such as volume is little, cost is low, no cumulative errors, so it has become one of main means of current attitude measurement.

Utilize GPS to realize the high precision relative positioning, must adopt measuring error at millimetre-sized carrier phase observation data, adopt two difference carrier phase observation equations can reduce ionosphere and tropospheric error effectively, orbit error, satellite and receiver clock error are normally used basic models in the attitude measurement.But because carrier wave is a kind of periodic sinusoidal signal, exist the integer ambiguity and the complete cycle saltus step problem of observation signal when carrying out phase measurement, this is the technological difficulties of carrier phase measurement just.

At present, find the solution attitude of carrier comparatively ripe two kinds of methods are arranged, a kind of is THE AMBIGUITY FUNCTION METHOD USED (AFM), advantage is to resolve single epoch, need not consider the cycle slip problem, shortcoming is that calculated amount is very big, and doctor Wang Yongquan of Shanghai Communications University improves this method in its PhD dissertation " GPS/GLONASS attitude measurement research under high dynamic condition during long boat ", reduced calculated amount greatly, but success ratio has much room for improvement still; Another is the LAMBDA algorithm, this method is proposed by P.J.G professor Teunissen of Delft Polytechnics at first, a plurality of afterwards scholars study and improve, be widely used in academia, the advantage of LAMBDA algorithm is to estimate the effective method of integer ambiguity, but also there are some shortcomings in actual applications in this method, first, the LAMBDA algorithm need be tried to achieve the floating-point of integer ambiguity in advance and be separated the variance-covariance matrix of separating with floating-point, for single frequency receiving, floating-point is separated obtains the observation data that often needs a plurality of epoch, promptly need certain initialization time, and utilize and resolve the baseline coordinate a plurality of epoch, must guarantee that number of satellite does not change in each of the solution procedure epoch, and cycle slip can not occur, but carrier is in motion process, inevitably be subjected to blocking of various barriers and cause the receiver losing lock and cycle slip takes place, perhaps satellite is because of blocking " invisible ".Second, the LAMBDA algorithm is comparatively ripe on static baseline attitude measurement, because the baseline coordinate remains unchanged at any time, utilizing least square to find the solution floating-point easily separates with the LAMBDA algorithm and estimates initial integer ambiguity, usually can in a few minutes, find the solution baseline coordinate and attitude angle, but under current intelligence, the baseline coordinate difference constantly all corresponding different unknown quantitys, classical least square method and LAMBDA algorithm can not directly be used, present existing method all needs long initialization time to finish the process that blur level converges to integer solution, is unfavorable for practical engineering application; The 3rd, the LAMBDA algorithm is found the solution the precision sensitivity that the success ratio of attitude of carrier is separated floating-point, and it is high more that floating-point is separated precision, and success ratio is high more; The 4th, adopt the LAMBDA algorithm, only utilize the carrier phase observed quantity in single epoch, to find the solution, can run into the order problem of losing of observation equation, can't obtain the blur level floating-point and separate.

The present invention still adopts the LAMBDA algorithm in order to guarantee success ratio, simultaneously in order to overcome the shortcoming of LAMBDA algorithm, adopts resolve single epoch, adopts new method to solve to find the solution floating-point single epoch to separate the order problem thanks to that is run into.Promptly utilize the sign indicating number observed reading of the problem that does not have integer ambiguity and cycle slip, though its measuring accuracy is than low 2～3 orders of magnitude of carrier wave, it is impracticable directly carrying out the high precision relative positioning with it, but the sign indicating number observation equation can be found the solution by subcarrier phase observations equation through conversion, makes to find the solution floating-point single epoch and separates.In theory, the precision of sign indicating number observed reading is high more, booster action to the carrier phase observation equation is strong more so, the success ratio of attitude algorithm is high more, and utilize carrier smoothing code pseudorange technology can improve the precision of yard observed reading, thereby help improving the success ratio that integer ambiguity is estimated, and then improve the performance of dynamically surveying the appearance algorithm.

Summary of the invention

Technology of the present invention is dealt with problems: overcome disadvantages of background technology, a kind of dynamic method for determining posture based on carrier smoothing code pseudorange technology is provided, the present invention utilizes pseudo-code observed quantity subcarrier phase observations equation to carry out list attitude algorithm epoch, the cycle slip that must consider in having avoided considering to find the solution a plurality of epoch detects and the reparation problem, and does not have the initialization time problem; Owing to only used observation data sometime, can obtain the attitude attitude in this moment, so the present invention can be used for the Real-time and Dynamic attitude measurement effectively; The present invention utilizes a yard observed quantity subcarrier phase observations amount, solved and found the solution the blur level floating-point single epoch and separate the order problem of losing that is run into, and can utilize the technology of carrier phase smoothing code pseudorange to improve the precision of sign indicating number observed quantity, and, further improve the success ratio that attitude of carrier is found the solution in conjunction with the method that enlarges blur level candidate solution space.

The objective of the invention is to be achieved through the following technical solutions: decide the appearance algorithmic method based on the dynamic of carrier smoothing code pseudorange technology, performing step is as follows:

(1) whether use three difference methods detect and have current epoch cycle slip to take place, if do not have, then use yard observed quantity after Hatch filtering obtains smoothly, and record smooth window length k; If have, then use the sign indicating number observed quantity of current epoch;

(2) variance-covariance matrix that floating-point is separated and floating-point is separated that utilizes sign indicating number observed quantity (the sign indicating number observed quantity of sign indicating number observed quantity after level and smooth or current epoch) in the step (1) and the carrier phase observed quantity of current epoch to find the solution integer ambiguity;

(3) with the floating-point of described integer ambiguity is separated and floating-point is separated variance-covariance matrix as the static solution of finding the solution blur level in the initial parameter substitution LAMBDA algorithm, p blur level candidate value (p selects 800 usually) before obtaining;

(4) blur level that p blur level candidate value before described carried out following steps is successively checked, until finding out the blur level candidate solution that satisfies constraint condition and resolving the attitude angle that obtains with this blur level candidate value:

(4.1) utilize the blur level candidate value to try to achieve the baseline vector, calculate the error find the solution the base length that obtains and true base length, if error true base length 1% in, then keep this blur level candidate value, otherwise reject this blur level candidate value;

(4.2) adopt the kernel method of inspection to calculate the residual error scalar value Ω of blur level candidate value in (4.1) _w, and by p blur level candidate value before the little bigger arrangement;

(4.3) utilize p blur level candidate value in (4.2) to calculate the baseline vector one by one, and by corresponding course angle Ψ of gained baseline vector calculation and pitching angle theta;

(4.4) the first blur level candidate value that satisfies the attitude angle constraint promptly for the carrier of ground motion, satisfies then as correctly separating | θ | and≤10 °; For the auxiliary carrier of inertia device is arranged, satisfy

And

Wherein

With

Be the angle of pitch and the course angle observed reading that inertia device provides, δ θ and δ Ψ are the error span that course angle Ψ and pitching angle theta are set; If this blur level candidate value does not satisfy constraint condition, then from (4.2), screen next blur level candidate value, continue to repeat (4.3), (4.4) step, until finding out blur level candidate solution that satisfies constraint condition and the attitude angle that calculates according to this blur level candidate solution.

The present invention's advantage compared with prior art is: mainly contain four contributions, first, used LAMBDA algorithm needs a plurality of epoch and find the solution the blur level floating-point to separate in the background technology, must solve cycle slip so and repair problem, the present invention adopts single method of resolving epoch, has avoided cycle slip and has repaired problem and allow the number of satellite of each epoch to change; The second, used LAMBDA algorithm comparative maturity on static attitude is measured is handled dynamic attitude measurement scarce capacity in the background technology, and the present invention can make it handle dynamic attitude measurement effectively; The 3rd, used LAMBDA algorithm is found the solution the precision sensitivity that the success ratio of attitude of carrier is separated floating-point in the background technology, the present invention is by expanding the search volume of LAMBDA algorithm, a kind of effective blur level verification algorithm is proposed, seek best integer ambiguity, overcome LAMBDA algorithm floating-point and separated precision and find the solution the shortcoming that the success ratio of attitude of carrier descends when not high enough; The 4th, utilized sign indicating number and carrier phase observed quantity simultaneously, solved and found the solution floating-point single epoch and separate the order problem of losing that is run into, and utilized carrier smoothing code pseudorange technology to improve the precision of yard observed reading, thereby help improving the precision that floating-point is separated, further improve and find the solution the success ratio of attitude of carrier.

Description of drawings

Fig. 1 is according to dynamic attitude measurement implementation method schematic flow sheet of the present invention;

Fig. 2 is according to integer ambiguity inspection process figure of the present invention.

Embodiment

Before introducing the present invention, preferably introduce correlated condition such as preceding topic that the present invention realizes or relevant knowledge etc. earlier.

As shown in Figure 1, specific implementation process of the present invention is as follows:

(1) whether use three difference methods detect and have current epoch cycle slip to take place, if do not have, then use yard observed quantity after Hatch filtering obtains smoothly, and record smooth window length k; If have, then use the sign indicating number observed quantity of current epoch;

Make δ φ be the three difference carrier phase measurement values of contiguous two epoch, δ ρ is three differences of two antennas to the geometric distance of satellite, can roughly calculate according to the motion state situation of carrier, and δ ε is three difference noise items (below the centimetre-sized), and λ is a carrier wavelength, ε _CBe default thresholding, C is two difference cycle slips, then when satisfying following formula

|C|＝|(δφ-δρ-δε)/λ|＞ε _C

It has been generally acknowledged that to detect cycle slip that should adopt the sign indicating number measured value that observes current epoch this moment, use formula (5) is calculated the blur level floating-point and separated.

For the epoch that does not detect cycle slip, use the sign indicating number observed quantity of carrier smoothing.Current time pseudorange observed reading is designated as

Utilize the observed reading of j epoch and the variation of carrier phase to estimate that the pseudorange value of current time is

Pseudorange note after level and smooth is done

The variation of carrier phase is Δ φ (k), makes that K is the maximal value of k, then has according to the Hatch filtering algorithm

When k≤K

$\stackrel{\‾}{\mathrm{\ρ}}\left(k\right)=\frac{1}{k}\underset{j=1}{\overset{k}{\mathrm{\Σ}}}{\widehat{\mathrm{\ρ}}}_j\left(k\right)=\frac{k-1}{k}[\stackrel{\‾}{\mathrm{\ρ}}(k-1)+\mathrm{\Δ\φ}\left(k\right)]+\frac{1}{k}\widetilde{\mathrm{\ρ}}\left(k\right)$

When k＞K

$\stackrel{\‾}{\mathrm{\ρ}}\left(k\right)=\frac{1}{K}\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\ρ}}}_j\left(k\right)=\frac{K-1}{K}[\stackrel{\‾}{\mathrm{\ρ}}(k-1)+\mathrm{\Δ\φ}\left(k\right)]+\frac{1}{K}\widetilde{\mathrm{\ρ}}\left(k\right)$

(the Federal Aviation Administration of Directorate of Air of the United States Federal, FAA) recommending smooth window maximal value K value is 100 seconds, but recommendation often is not best, depend on that specifically the GPS that when and where carries out measures, the user can select the size of K value according to the actual conditions of oneself.

(2) variance-covariance matrix that floating-point is separated and floating-point is separated that utilizes sign indicating number observed quantity (the sign indicating number observed quantity of sign indicating number observed quantity after level and smooth or current epoch) in the step (1) and the carrier phase observed quantity of current epoch to find the solution integer ambiguity;

For being installed on the carrier with two antennas of A, B is the short baseline of end points, is expressed as follows for the single carrier phase observations equation of satellite i

Wherein,

Be the fraction parts of two antennas of A, B to the poor carrier phase of list of satellite i, Δ N _AB ⁱBe the poor integer ambiguity of list to be estimated, s ⁱBe the unit vector of antenna to satellite i, λ is a carrier wavelength, and b is the baseline vector, β _AB ^φBe the observational error that causes by two receiver clock correction, v _AB ⁱIt is observation noise.For m satellite, m single eikonal equation arranged then.Mathematical model is as follows:

$y^{\mathrm{\φ}}=E\·b-N_{\mathrm{SD}}+e{\mathrm{\β}}_{\mathrm{AB}}^{\mathrm{\φ}}+v_{\mathrm{AB}}^{\mathrm{\φ}},v_{\mathrm{AB}}^{\mathrm{\φ}}~N\left(\mathrm{0,2}{\mathrm{\σ}}_{\mathrm{\φ}}^2{I}_m\right)---\left(1\right)$

Wherein,

Single poor ambiguity vector

The observation noise vector is

E=(1,1 ..., 1) ^T, receiver is as follows to the design matrix of satellite:

$E=\frac{1}{\mathrm{\λ}}\left[\begin{array}{c}{\left(s^1\right)}^T\\ \·\\ \·\\ \·\\ {\left(s^m\right)}^T\end{array}\right]$

In order to cut down clock correction item β _AB ^φ, need carry out the Householder conversion, specific as follows:

$\mathrm{Pe}=\sqrt{m}{e}_1,P\≡I-\frac{2{\mathrm{uu}}^T}{u^{T}u},u\≡e_1-\frac{1}{\sqrt{m}}e$

P ∈ R wherein ^{M * m}, e ₁=(1,0 ... 0) ^T, have so

$P=\left[\begin{array}{cc}\frac{1}{\sqrt{m}}& \frac{e^T}{\sqrt{m}}\\ \frac{e}{\sqrt{m}}& I_{m-1}-\frac{{\mathrm{ee}}^T}{m-\sqrt{m}}\end{array}\right]\≡\left[\begin{array}{c}{p}^T\\ \stackrel{\‾}{P}\end{array}\right],$ Wherein $\stackrel{\‾}{P}=\left[\begin{array}{cc}\frac{e}{\sqrt{m}}& I_{m-1}-\frac{{\mathrm{ee}}^T}{m-\sqrt{m}}\end{array}\right].$

With (1) formula both sides premultiplication P matrix, promptly have

$\left[\begin{array}{c}{p}^T{y}^{\mathrm{\φ}}\\ \stackrel{\‾}{P}{y}^{\mathrm{\φ}}\end{array}\right]=\left[\begin{array}{c}{p}^{T}E\\ \stackrel{\‾}{P}E\end{array}\right]b-\left[\begin{array}{c}{p}^T\\ \stackrel{\‾}{P}\end{array}\right]N_{\mathrm{SD}}+\left[\begin{array}{c}1\\ 0\end{array}\right]\sqrt{m}{\mathrm{\β}}_{\mathrm{AB}}^{\mathrm{\φ}}+\left[\begin{array}{c}{p}^T{v}_{\mathrm{AB}}^{\mathrm{\φ}}\\ \stackrel{\‾}{P}{v}_{\mathrm{AB}}^{\mathrm{\φ}}\end{array}\right]$

The Householder conversion does not change the statistical property of noise, and the extracting section that does not contain the clock correction item in the following formula is come out, and then has

$\stackrel{\‾}{P}{y}^{\mathrm{\φ}}=\stackrel{\‾}{P}\mathrm{Eb}-\stackrel{\‾}{P}{N}_{\mathrm{SD}}+\stackrel{\‾}{P}{v}_{\mathrm{AB}}^{\mathrm{\φ}},\stackrel{\‾}{P}{v}_{\mathrm{AB}}^{\mathrm{\φ}}~N\left(\mathrm{0,2}{\mathrm{\σ}}_{\mathrm{\φ}}^2{I}_{m-1}\right)---\left(2\right)$

Definition And according to the definition of two poor integer ambiguities, promptly

$N_{\mathrm{DD}}={({\mathrm{\ΔN}}_{\mathrm{AB}}^2-{\mathrm{\ΔN}}_{\mathrm{AB}}^1,{\mathrm{\ΔN}}_{\mathrm{AB}}^3-{\mathrm{\ΔN}}_{\mathrm{AB}}^1\·\·\·,{\mathrm{\ΔN}}_{\mathrm{AB}}^m-{\mathrm{\ΔN}}_{\mathrm{AB}}^1)}^T$ Prove easily

$\stackrel{\‾}{P}=\mathrm{FJ},\stackrel{\‾}{P}{N}_{\mathrm{SD}}={\mathrm{FJN}}_{\mathrm{SD}}={\mathrm{FN}}_{\mathrm{DD}}$

Above-mentioned relation substitution (2) formula is then had

$\stackrel{\‾}{P}{y}^{\mathrm{\φ}}=\stackrel{\‾}{P}\mathrm{Eb}-{\mathrm{FN}}_{\mathrm{DD}}+\stackrel{\‾}{P}{v}_{\mathrm{AB}}^{\mathrm{\φ}}---\left(3\right)$

Similar with (1), use pseudo range observed quantity, obtain pseudorange list difference observation equation

$y^{\mathrm{\ρ}}=E\·b+e{\mathrm{\β}}_{\mathrm{AB}}^{\mathrm{\ρ}}+v_{\mathrm{AB}}^{\mathrm{\ρ}},v_{\mathrm{AB}}^{\mathrm{\ρ}}~N(0,{\mathrm{\σ}}_{\mathrm{\ρ}}^2{I}_{m-1})---\left(4\right)$

Wherein, single poor pseudorange observation vector is

Similar with (2), obtain

$\stackrel{\‾}{P}{y}^{\mathrm{\ρ}}=\stackrel{\‾}{P}\mathrm{Eb}+\stackrel{\‾}{P}{v}_{\mathrm{AB}}^{\mathrm{\ρ}}$

Definition σ ≡ σ _φ/ σ _ρ, σ wherein _φAnd ρ _σRepresent the standard deviation of carrier wave and sign indicating number observed reading respectively, σ is the ratio of the two, then has

$\left[\begin{array}{c}\stackrel{\‾}{P}{y}^{\mathrm{\φ}}\\ \mathrm{\σ}\stackrel{\‾}{P}{y}^{\mathrm{\ρ}}\end{array}\right]=\left[\begin{array}{c}\stackrel{\‾}{P}E\\ \mathrm{\σ}\stackrel{\‾}{P}E\end{array}\right]b-\left[\begin{array}{c}F\\ 0\end{array}\right]N_{\mathrm{DD}}+\left[\begin{array}{c}\stackrel{\‾}{P}{v}^{\mathrm{\φ}}\\ \mathrm{\σ}\stackrel{\‾}{P}{v}^{\mathrm{\ρ}}\end{array}\right],\left[\begin{array}{c}\stackrel{\‾}{P}{v}^{\mathrm{\φ}}\\ \mathrm{\σ}\stackrel{\‾}{P}{v}^{\mathrm{\ρ}}\end{array}\right]~N\left(\mathrm{0,2}{\mathrm{\σ}}_{\mathrm{\φ}}^2{I}_{2(m-1)}\right)$

Be equivalent to following form

$\left[\begin{array}{c}\stackrel{\‾}{P}{y}^{\mathrm{\φ}}\\ \mathrm{\σ}\stackrel{\‾}{P}{y}^{\mathrm{\ρ}}\end{array}\right]=\left[\begin{array}{cc}\stackrel{\‾}{P}E& F\\ \mathrm{\σ}\stackrel{\‾}{P}E& 0\end{array}\right]\left[\begin{array}{c}b\\ N_{\mathrm{DD}}\end{array}\right]+\left[\begin{array}{c}\stackrel{\‾}{P}{v}^{\mathrm{\φ}}\\ \mathrm{\σ}\stackrel{\‾}{P}{v}^{\mathrm{\ρ}}\end{array}\right]---\left(5\right)$

The equation number is that 2 (m-1) are individual in the following formula, and the unknown number number is (m-1)+3=m+2, so just can find the solution integer ambiguity as long as m 〉=4 are visible number of satellites more than or equal to 4 the time.It is generally acknowledged the empirical value σ=0.01. of the standard deviation scale factor of carrier wave and sign indicating number observed reading

If adopt the sign indicating number pseudorange behind the carrier smoothing, then (5) formula should have mutually

$\left[\begin{array}{c}\stackrel{\‾}{P}{y}^{\mathrm{\φ}}\\ \stackrel{\‾}{\mathrm{\σ}}\stackrel{\‾}{P}{y}^{\stackrel{\‾}{\mathrm{\ρ}}}\end{array}\right]=\left[\begin{array}{cc}\stackrel{\‾}{P}E& F\\ \stackrel{\‾}{\mathrm{\σ}}\stackrel{\‾}{P}E& 0\end{array}\right]\left[\begin{array}{c}b\\ N_{\mathrm{DD}}\end{array}\right]+\left[\begin{array}{c}\stackrel{\‾}{P}{v}^{\mathrm{\φ}}\\ \stackrel{\‾}{\mathrm{\σ}}\stackrel{\‾}{P}{v}^{\stackrel{\‾}{\mathrm{\ρ}}}\end{array}\right]---\left(6\right)$

Sign indicating number noise after using k epoch level and smooth becomes original

Then

Make observation vector Wait to estimate the matrix of coefficients of parameter

Noise vector

The variance-covariance matrix of noise is designated as Q _Y, then formula (6) can be regarded following form as

Y＝Ax+w，w～Q _Y

Least square solution is $\hat{x}={\left(A^T{Q}_Y^{-1}A\right)}^{-1}{A}^T{Q}_Y^{-1}Y$

Variance-covariance matrix is $Q_{\hat{x}}={\left(A^T{Q}_Y^{-1}A\right)}^{-1}$

Because least square is not considered the integer characteristic of two difference blur leveles, what therefore obtain is the variance-covariance matrix that floating-point is separated and floating-point is separated of two difference blur leveles, as follows

$\hat{x}=\left[\begin{array}{c}\hat{b}\\ \hat{N}\end{array}\right]$ With $Q_{\hat{x}}=\left[\begin{array}{cc}{Q}_{\hat{b}}& Q_{\hat{b}\hat{N}}\\ Q_{\hat{N}\hat{b}}& Q_{\hat{N}}\end{array}\right]$

(3) with the floating-point of described integer ambiguity is separated and floating-point is separated variance-covariance matrix as the static solution of finding the solution blur level in the initial parameter substitution LAMBDA algorithm, (p selects 800 to p blur level candidate value usually before obtaining, rule of thumb, this value select 800 not only can comprise correctly separate but also can not cause the calculated amount excessive and very consuming time);

The floating-point of two poor blur leveles separated be fixed into integer solution, promptly carry out integer ambiguity and estimate, at present, the LAMBDA algorithm is that integer ambiguity is estimated one of the most effective algorithm, and the objective function minimum below making is tried to achieve the blur level static solution:

$\underset{N}{\min }{(\hat{N}-N)}^T{Q}_N^{-1}(\hat{N}-N),N\∈Z^n$

Wherein

Reflected

Precision, Precision sufficiently high the time, with the LAMBDA algorithm search to the optimal candidate point be correctly separating of blur level.The precision that single floating-point that provides epoch is separated is lower, and therefore, the optimal candidate that the LAMBDA algorithm provides is separated often incorrect.Enlarge the candidate value space of LAMBDA algorithm in this algorithm,

Make N ^(j)Be j candidate point, definition

P candidate point N ^(p)Satisfy following formula r ⁽¹⁾＜...＜r ^(j)＜... r ^(p), the way that each candidate point is checked is one by one determined correct integer ambiguity.

(4) blur level that p blur level candidate value before described carried out following steps is successively checked, concrete blur level inspection process figure as shown in Figure 2:

(4.1) utilize the blur level candidate value to try to achieve the baseline vector, calculate the error find the solution the base length that obtains and true base length, if error true base length 1% in, then keep this blur level candidate value, otherwise reject this blur level candidate value;

The blur level candidate value that promptly satisfies following formula will be selected

$b_l-\mathrm{\δ}{b}_l\≤\left|\widetilde{b_l}\right|\≤b_l+{\mathrm{\δb}}_l$

In the formula: δ b _lBe given threshold value,

Be the base length that calculates, b _lIt is true base length.Because uncertain information is comprised in the blur level search volume after the expansion, in attitude measurement is used, δ b _lTo choose be the key of base length constraint.Because the variation of antenna phase center and noise effect, we can not be with δ b _lToo small, the simultaneously excessive δ b that is provided with of value _lCan not reduce the blur level candidate value effectively again.This value need be chosen according to the measurement environment of reality.Common δ b _lBe b _l1%.

(4.2) adopt the kernel method of inspection to calculate the residual error scalar value Ω of blur level candidate value in (4.1) _w, and by p blur level candidate value of little bigger arrangement;

Single eikonal equation of the carrier phase of non-reference star and reference star are subtracted each other, can obtain two difference observation observation equations, as follows

y+N _DD＝H·b+v，v～N(0，Q _y)

Wherein, two poor carrier phase observation data vectors

Two poor integer ambiguity vectors Two poor observation noise vectors are

H is that receiver is as follows to the design matrix of satellite:

$H=\frac{1}{\mathrm{\λ}}\left[\begin{array}{c}{\left(s^2\right)}^T-{\left(s^1\right)}^T\\ \·\\ \·\\ \·\\ {\left(s^m\right)}^T-{\left(s^1\right)}^T\end{array}\right]$

A given N _DD=N ₀, can calculate baseline and be

$b={\left(H^T{Q}_y^{-1}H\right)}^{-1}{H}^T{Q}_y^{-1}(y+N_0)$

Order

Then residual error is

v＝(y+N ₀)-HA(y+N ₀)＝(I-HA)(y+N ₀)

Therefore, the weighted sum of squares of residual error is

${\mathrm{\Ω}}_v=v^T{Q}_y^{-1}v={(y+N_0)}^{T}B(y+N_0),$ Wherein $B={(I-\mathrm{HA})}^T{Q}_y^{-1}(I-\mathrm{HA})$

If the kernel of B is V, structure projection operator P=V ^TV, then the vertical component of projection is w=P (y+N _o)-(y+N _o)

For real N _DD, then make following statistic for minimum

${\mathrm{\Ω}}_w=w^T{Q}_y^{-1}w$

In the reality test, because The noise, separating really may not be to make Ω _wMinimum N _DD, make Ω _wAll less N _DDAll need to do further check.

(4.3) utilize the blur level candidate value in (4.2) to calculate the baseline vector one by one, and by the corresponding course angle Ψ of baseline vector calculation and the pitching angle theta of gained;

1. according to residual error by little bigger arrangement before p blur level candidate value

2. one by one with candidate value substitution formula (30), the baseline vector that obtains

Under east northeast sky coordinate system, be expressed as

Then final attitude angle can be found the solution with following formula:

Course angle is $\mathrm{\ψ}=\arctan \left(\frac{b_E}{b_N}\right)$ The angle of pitch is $\mathrm{\θ}=\arctan \left(\frac{b_U}{\sqrt{{\left(b_N\right)}^2+{\left(b_E\right)}^2}}\right)$

(4.4) the first blur level candidate value that satisfies the attitude angle constraint promptly for the carrier of ground motion, satisfies then as correctly separating | θ | and≤10 °; For the auxiliary carrier of inertia device is arranged, satisfy

And Wherein

With

Be the angle of pitch and the course angle observed reading that inertia device provides, δ θ and δ Ψ are the error span that course angle Ψ and pitching angle theta are set; If this blur level candidate value does not satisfy constraint condition, then from (4.2), screen next blur level candidate value, continuation repeats (4.3), (4.4) step detects, until finding out blur level candidate solution that satisfies constraint condition and the attitude angle that calculates according to this blur level candidate solution.

The non-elaborated part of the present invention belongs to present technique field personnel's known technology.

Claims (2)

1. dynamic method for determining posture based on carrier smoothing code pseudorange technology is characterized in that performing step is as follows:

(1) whether use three difference methods detect and have current epoch cycle slip to take place, if do not have, then use yard observed quantity after Hatch filtering obtains smoothly, and record smooth window length k; If have, then use the sign indicating number observed quantity of current epoch;

(2) utilize sign indicating number observed quantity in the step (1), comprise the variance-covariance matrix that floating-point is separated and floating-point is separated that integer ambiguity is found the solution in sign indicating number observed quantity after level and smooth or the sign indicating number observed quantity of current epoch and the carrier phase observed quantity of current epoch;

(3) with the floating-point of described integer ambiguity is separated and floating-point is separated variance-covariance matrix as the static solution of finding the solution blur level in the initial parameter substitution LAMBDA algorithm, p blur level candidate value before obtaining;

(4) blur level that p blur level candidate value before described carried out following steps is successively checked, until finding out the blur level candidate solution that satisfies constraint condition and resolving the attitude angle that obtains with this blur level candidate value:

(4.1) utilize the blur level candidate value to try to achieve the baseline vector, calculate the error find the solution the base length that obtains and true base length, if error true base length 1% in, then keep this blur level candidate value, otherwise reject this blur level candidate value;

(4.2) adopt the kernel method of inspection to calculate the residual error scalar value Ω of blur level candidate value in (4.1) _w, and by p blur level candidate value before the little bigger arrangement;

(4.3) utilize p blur level candidate value in (4.2) to calculate the baseline vector one by one, and by corresponding course angle ψ of gained baseline vector calculation and pitching angle theta;

(4.4) the first blur level candidate value that satisfies the attitude angle constraint promptly for the carrier of ground motion, satisfies then as correctly separating | θ | and≤10 °; For the auxiliary carrier of inertia device is arranged, satisfy

And

Wherein

With Be the angle of pitch and the course angle observed reading that inertia device provides, δ θ and δ ψ are the error span that course angle ψ and pitching angle theta are set; If this blur level candidate value does not satisfy constraint condition, then from (4.2), screen next blur level candidate value, continue to repeat (4.3), (4.4) step, until finding out blur level candidate solution that satisfies constraint condition and the attitude angle that calculates according to this blur level candidate solution.

2. according to the described dynamic method for determining posture based on carrier smoothing code pseudorange technology of claim 1, it is characterized in that: described p selects 800.

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