CN102749634A - Pseudo-range acceleration failure detecting method in satellite navigation region reinforcement system - Google Patents

Abstract

The invention provides a pseudo-range acceleration failure detecting method in a satellite navigation region reinforcement system, wherein the failure detecting method comprises the steps of: counting the code pseudo-range correction values of various collecting moment within a preset time slot to obtain the sequential probable value of happening failure, and comparing the sequential probable value with a preset out-of-control threshold to obtain an offset statistic value, and then, comparing the offset statistic value with a preset judging range threshold to generate a pseudo-range acceleration failure signal, the detecting method objectively processes the obtained data to detect the failure, and compared with the current detecting method based on differential detection algorithm, the detecting method needs not to select corresponding parameters by experience, thereby improving the detecting performance of the pseudo-range acceleration failure.

Description

Pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System

Technical field

The present invention relates to the satellite navigation system structure technology, relate in particular to pseudorange acceleration fault detection method in a kind of satellite navigation Local Area Augmentation System.

Background technology

Fast development along with social economy and aviation industry; Airport distribution density all over the world increases; Like area, China Pearl River Delta; Five airports are distributing in radius is no more than 200 kilometers scope: airport, Zhuhai, Shenzhen Airport, airport, Guangzhou, airport, Hong Kong and airport, Macao, this just requires high-grade as far as possible navigator fix service, moves efficiently to guarantee each airport security.For this reason; The scholar of BJ University of Aeronautics & Astronautics has proposed a kind of satellite navigation Local Area Augmentation System (Regional Augmentation System; Be called for short RAS); This system arranges a plurality of monitoring stations in the zone; Utilize the information of adjacent, part or all of monitoring station and control information that WAAS (Wide Area Augmentation System is called for short WAAS) is broadcast to improve navigation performance, to satisfy the demand of aircraft precision approach stage and landing period to aircraft in the whole zone.

In the RAS course of work; Because the influence with factor such as earth rotation is delayed in satellite clock correction, ionosphere and troposphere; There is error in the navigation data that RAS is obtained; Break down if error is promptly thought above institute of system tolerance, wherein, pseudorange acceleration fault is a kind of important fault in the fault of range finding source, ground.

Pseudorange acceleration fault is for increase fault (Slowly Growing Error slowly; SGE), the so-called fault that increases slowly refers in time growth and increase gradually, and this type fault can not produce bigger influence to the system location when beginning; Therefore being difficult in early detection arrives; And when this type fault is accumulated to a certain degree, might constitute the multiple faults situation that be difficult to detect with new fault, cause the integrity of whole RAS system to be lost with continuity.Therefore, it is extremely important this type fault to be carried out early detection.

At present; Mainly be based on the detection method of Differential Detection algorithm for the detection method of pseudorange acceleration fault; But the detection statistic in the Differential Detection algorithm for the square-error root sum square of trying to achieve based on the least square localization method in former and later two differences constantly; These former and later two constantly choosing of difference is to obtain by rule of thumb not have accurate computing method, therefore causes through the detection unstable properties of this method to pseudorange acceleration fault.

Summary of the invention

The invention provides pseudorange acceleration fault detection method in a kind of satellite navigation Local Area Augmentation System, to improve detection performance to pseudorange acceleration fault.

This fault detection method comprises:

The difference of the actual distance value at each collection moment ground monitoring station yard pseudo-range measurements and satellite and ground monitoring station is to obtain the data sequence of being made up of each said collection sign indicating number pseudo-range corrections value constantly in the said Preset Time section in the calculating Preset Time section;

To put the seclected time in the said Preset Time section is that cut-point is divided into first data sequence and second data sequence with said data sequence;

Said first data sequence and second data sequence are carried out statistical treatment, obtain the average and the standard deviation of said first data sequence and second data sequence;

Average and standard deviation according to said first data sequence and second data sequence are obtained the sequential probability that breaks down;

Said sequential probability that breaks down and preset threshold value out of control are compared, obtain the side-play amount statistical value;

Know said side-play amount statistical value when judgement and when judging, generate pseudorange acceleration fault-signal apart from threshold value greater than preset.

Pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that the embodiment of the invention provides; Through being carried out statistical treatment, each collection sign indicating number pseudo-range corrections value constantly in the Preset Time section obtains the sequential probability value that breaks down; And then obtain the side-play amount statistical value through the sequential probability value is compared with preset threshold value out of control, then, with the side-play amount statistical value with preset judge compare apart from threshold value; To generate pseudorange acceleration fault-signal; This kind detection method is through detection failure being carried out in the objective processing of obtaining data, compare with existing detection method based on the Differential Detection algorithm, need not to choose by rule of thumb relevant parameters; Therefore, can improve detection performance to pseudorange acceleration fault.

Description of drawings

Fig. 1 is the process flow diagram of pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that the embodiment of the invention provided;

Fig. 2 is the process flow diagram of pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that further embodiment of this invention provided.

Embodiment

Satellite navigation Local Area Augmentation System a kind of satellite navigation system that development is come out on original satellite WAAS basis; This system arranges a plurality of ground monitorings station in the zone; Utilize the information of adjacent, part or all of monitoring station and control information that WAAS is broadcast to improve navigation performance, to satisfy the demand of aircraft precision approach stage and landing period to aircraft in the whole zone.

Mainly comprise a plurality of ground monitorings station, satellite navigation receiver and master station etc. in this system.Satellite navigation receiver can receive the navigation signal and the navigation data of satellites transmits.The ground monitoring station can be used for obtaining orbit determination, the satellite clock inferior relation Monitoring Data to basic functions such as satellite navigation system navigation, location; And the mode of communication via satellite or ground communication is sent to master station; After master station is handled the data at each ground monitoring station again; Up injection satellite is to carry out precise orbit determination to satellite.

This system in the course of the work; Because the influence with factor such as earth rotation is delayed in satellite clock correction, ionosphere and troposphere, makes the navigation data that obtains have error, if error is promptly thought above institute of system tolerance breaks down; Wherein, Pseudorange acceleration fault is a kind of important fault in the fault of range finding source, ground, and the embodiment of the invention provides a kind of detection method, is used for the pseudorange acceleration fault of satellite navigation Local Area Augmentation System is detected.

Fig. 1 is the process flow diagram of pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that the embodiment of the invention provided, and as shown in Figure 1, this detection method comprises:

The difference of the actual distance value at each collection moment ground monitoring station yard pseudo-range measurements and satellite and ground monitoring station is to obtain the data sequence of being made up of each said collection sign indicating number pseudo-range corrections value constantly in the said Preset Time section in step 10, the calculating Preset Time section.

Ground monitoring station yard pseudo-range measurements is the sign indicating number pseudorange value at satellite navigation receiver obtains after the data that receive are decoded in the satellite navigation Local Area Augmentation System ground monitoring station, and the actual distance value at satellite and ground monitoring station is the satellite that calculates of the satellite position that calculates of almanac parameters that satellite navigation receiver is broadcast according to satellite and known ground monitoring station location and the actual range between the ground monitoring station.

Can be through each gathers the ground monitoring station yard pseudo-range measurements constantly and the actual distance value at satellite and ground monitoring station in the memory device stores Preset Time section; This Preset Time section can be several seconds, a few minutes or other times according to the needs setting that detects.

Computing machine that can be through comprising relative program or data processor etc. obtain two kinds of above-mentioned data from memory storage; Then; Calculate the difference between the actual distance value of each monitoring station, ground sign indicating number pseudo-range measurements and satellite and each monitoring station, ground; Each difference is promptly as each yard pseudo-range corrections value, and each yard pseudo-range corrections value is formed a data sequence with this.

Step 20, be that cut-point is divided into first data sequence and second data sequence with said data sequence with the seclected time in said Preset Time section point.

Step 30, said first data sequence and second data sequence are carried out statistical treatment, obtain the average and the standard deviation of said first data sequence and second data sequence.

Represent the data sequence formed by each yard pseudo-range corrections value with PRCTS below, use PrctS _iRepresent that i gathers sign indicating number pseudo-range corrections value constantly, sign indicating number pseudo-range corrections value is normally caused by satellite clock correction, receiver clock correction, ionospheric error, tropospheric error, ephemeris error and thermal noise error etc.At this, can suppose that above-mentioned these errors are separate random elements, it is a certain numerical value that average μ is obeyed in the data sequence distribution that then above-mentioned each yard pseudo-range corrections value is formed, and standard deviation sigma is the Gaussian distribution of a certain constant, and promptly this data sequence is PRctS ₁, PRctS ₂..., PRctS _i~ N (μ, σ).

Be cut-point with the t of point sometime in the Preset Time section below; Choosing of this time point t can be provided with as required; This data sequence is divided into two groups; Be respectively the first data sequence PRCTS1 and the second data sequence PRCTS2, and obtain average and the standard deviation of the first data sequence PRCTS1 and the second data sequence PRCTS2 respectively after two data sequences are handled, be i.e. first data sequence PRCTS1 ~ N (μ ₁, σ ₁), second data sequence PRCTS2 ~ N (μ ₂, σ ₂).

Suppose to produce behind the t of point sometime of pseudorange acceleration fault in the Preset Time section, then to meet average be μ to each yard pseudo-range corrections value before the t time point ₁With standard deviation be σ ₁Normal distribution, i.e. PRctS ₁, PRctS ₂..., PRctS _t~ N (μ ₁, σ ₁), and each yard pseudo-range corrections value after the t time point to meet average be μ ₂And standard deviation sigma ₂For normal distribution, i.e. PRctS _T+1, PRctS _T+2..., PRctS _m~ N (μ ₂, σ ₂), wherein, m representes the end time of this Preset Time section.

Meet the normal distribution of same type like first DS and second DS; Promptly the average of first data sequence and standard deviation equate with the average and the standard deviation of second data sequence; Explain that system is in slave mode in this Preset Time section always, pseudorange acceleration fault does not take place; If first DS and second DS meet dissimilar normal distributions; Promptly the average and the standard deviation of the average of first data sequence and standard deviation and second data sequence are unequal; Then explain behind the time point t in this Preset Time section out of controlly after the system, pseudorange acceleration fault possibly take place.

Step 40, obtain the sequential probability value that breaks down according to the average and the standard deviation of said first data sequence and second data sequence.

For the convenience of calculating, can handle each yard pseudo-range corrections value in first data sequence and second data sequence, use y below _iExpression is i sign indicating number pseudo-range corrections value constantly after treatment, sets

And, make σ ₂ ²=α ²σ ₁ ², μ ₂-μ ₁=δ σ ₁, wherein, α representes the deviation ratio of standard deviation of standard deviation and second data sequence of first data sequence, δ representes the deviation ratio of average of average and second data sequence of first data sequence.

Can obtain the sequential probability value P that breaks down through following computing formula based on the sequential probability ratio test theory through after the above-mentioned processing.

$P=\frac{L_2({\mathrm{\&mu;}}_2,{\mathrm{\&sigma;}}_2)}{L_1({\mathrm{\&mu;}}_1,{\mathrm{\&sigma;}}_1)}=\frac{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">t</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}}\exp (-\frac{{{\mathrm{<figure-callout\; id="2"\; label="y\; i"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">y</figure-callout>}}_i}^2}{2})\underset{i=t+1}{\overset{\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">m</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}\mathrm{\&alpha;}}\exp (-\frac{y_i-\mathrm{\&delta;}}{{2\mathrm{\&alpha;}}^2})}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">m</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}}\exp (-\frac{{{\mathrm{<figure-callout\; id="2"\; label="y\; i"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">y</figure-callout>}}_i}^2}{2})}$

$={\left(\frac{1}{\mathrm{\&alpha;}}\right)}^{m-t}\mathrm{Exp}[-\frac{1}{2{\mathrm{\&alpha;}}^2}\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}{(y_i-\mathrm{\&delta;})}^2+\frac{1}{2}\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}{y_i}^2],$ Wherein, $\mathrm{\&delta;}=\frac{{\mathrm{\&mu;}}_2-{\mathrm{\&mu;}}_1}{{\mathrm{\&sigma;}}_1},$ $\mathrm{\&alpha;}=\sqrt{\frac{{\mathrm{\&sigma;}}_2}{{\mathrm{\&sigma;}}_1}}.$

Step 50, said sequential probability that breaks down and preset threshold value out of control are compared, obtain the side-play amount statistical value.

Above-mentioned preset threshold value A out of control is a setting constant value, can be tried to achieve by false dismissal probability β and probability of false detection χ, is specially A=(1-β)/χ.

For the value of β and χ, can confirm that to the requirement of integrity index if need satisfy the integrity index of CAT I, then β and χ can be 10 according to the satellite navigation Local Area Augmentation System ^-4, if make this system satisfy the integrity index of CAT II/III, then β and χ can be 10 ^-6

After obtaining the sequential probability value P that breaks down; A this sequential probability value and a preset threshold value A out of control are compared; Further to obtain the side-play amount statistical value; This side-play amount statistical value possibly cause for squinting on the average, also possibly cause for squinting under the average, is the accumulation of the side-play amount in the Preset Time section.

Step 60, know said side-play amount statistical value when judgement and when judging, generate pseudorange acceleration fault-signal apart from threshold value greater than preset.

After obtaining above-mentioned side-play amount statistical value; Perhaps

compares apart from threshold value H with preset judgement with

; Wherein, The value of H can be for

if judge

perhaps

greater than judging apart from threshold value H then; Then pseudorange acceleration fault has taken place in explanation; To generate a pseudorange acceleration fault-signal this moment; With prompting related work personnel; Therefore the staff notes; In time take appropriate measures, to eliminate this fault.

Can know by technique scheme; Pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that the embodiment of the invention provides obtains the sequential probability value that breaks down through each collection sign indicating number pseudo-range corrections value constantly in the Preset Time section is carried out statistical treatment, and then obtains the side-play amount statistical value through the sequential probability value is compared with preset threshold value out of control; Then; Side-play amount statistical value and preset judgement are compared apart from threshold value, and to generate pseudorange acceleration fault-signal, this kind detection method is through detection failure is carried out in the objective processing of obtaining data; Compare with existing detection method based on the Differential Detection algorithm; Need not to choose by rule of thumb relevant parameters, therefore, can improve detection performance pseudorange acceleration fault.

Fig. 2 is the process flow diagram of pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System that further embodiment of this invention provided; As shown in Figure 2; On the basis of Fig. 1 embodiment; Further, in the above-mentioned steps 30 said first data sequence and second data sequence being carried out statistical treatment can comprise with average and the standard deviation of obtaining said first data sequence and second data sequence:

Step 301, basis

Obtain the average μ of said first data sequence ₁

Step 302, basis

Obtain the standard deviation sigma of said first data sequence ₁

Step 303, basis

Obtain the average μ of said second data sequence ₂

Step 304, basis

Obtain the standard deviation sigma of said second data sequence ₂

Wherein, t representes the time point in the said Preset Time section, and m representes the end time of said Preset Time section, PRctS _iRepresent that i gathers sign indicating number pseudo-range corrections value constantly.

And as shown in Figure 2, the sequential probability value that breaks down according to the average and the standard deviation calculating of said first data sequence and second data sequence in the above-mentioned step 40 comprises:

Step 401, basis

are obtained the sequential probability value P that breaks down; Wherein,

In the present embodiment, at first each yard pseudo-range corrections value in first data sequence and second data sequence is handled, used y _iExpression is i sign indicating number pseudo-range corrections value constantly after treatment, sets

And, make σ ₂ ²=α ²σ ₁ ², μ ₂-μ ₁=δ σ ₁, pass through computing formula according to the sequential probability ratio test theory through after the above-mentioned processing

Can obtain the sequential probability value P that breaks down.

As shown in Figure 2, in the above-mentioned step 50 said sequential probability that breaks down and preset threshold value out of control are compared, obtain the side-play amount statistical value and comprise:

When sequential probability value P is known in judgement greater than preset threshold value out of control; Obtain side-play amount statistical value

or

wherein through

or

; I>=t+1,

In the present embodiment, through $P=\frac{L_2({\mathrm{\&mu;}}_2,{\mathrm{\&sigma;}}_2)}{L_1({\mathrm{\&mu;}}_1,{\mathrm{\&sigma;}}_1)}=\frac{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">t</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}}\mathrm{Exp}(-\frac{{{\mathrm{<figure-callout\; id="2"\; label="y\; i"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">y</figure-callout>}}_i}^2}{2})\underset{i=t+1}{\overset{\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">m</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}\mathrm{\&alpha;}}\mathrm{Exp}(-\frac{y_i-\mathrm{\&delta;}}{{2\mathrm{\&alpha;}}^2})}{\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">m</figure-callout>}}{\mathrm{\&Pi;}}}\frac{1}{\sqrt{2\mathrm{\&pi;}}}\mathrm{Exp}(-\frac{{{\mathrm{<figure-callout\; id="2"\; label="y\; i"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">y</figure-callout>}}_i}^2}{2})}$ After obtaining sequential probability value P, cause that standard deviation is constant if pseudorange acceleration fault is a mean shift, this moment δ ≠ 0, α ²=1, then can know the sequential probability value that breaks down according to above-mentioned formula $P=\mathrm{Exp}\left[\mathrm{\&delta;}\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}{(y_i-\frac{\mathrm{\&delta;}}{2})}^2\right].$

A this sequential probability value and a preset threshold value out of control are compared; If P>=A; Promptly

can know through finding the solution above-mentioned equation; If δ greater than 0, is on the average squint, then can solve:

$\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}(y_i-\frac{\mathrm{\&delta;}}{2})\&GreaterEqual;\frac{\ln A}{\mathrm{\&delta;}},$

At this moment, can obtain side-play amount statistical value

according to the following recursion formula of structure

${\mathrm{<figure-callout\; id="1"\; label="D"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">D</figure-callout>}}_{1,(i+1)}^{+}=\mathrm{Max}[0,{\mathrm{<figure-callout\; id="1"\; label="D"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">D</figure-callout>}}_{1,i}^{+}+(y_{i+1}-\frac{\mathrm{\&delta;}}{2})],$ Wherein, (i>=t+1),

If δ less than 0, is under the average and squints, then can solve:

$\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}(y_i-\frac{\mathrm{\&delta;}}{2})\&le;\frac{\ln A}{\mathrm{\&delta;}},$

At this moment, can obtain side-play amount statistical value according to the following recursion formula of structure

${\mathrm{<figure-callout\; id="1"\; label="D"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">D</figure-callout>}}_{1,(i+1)}^{-}=\mathrm{Max}[0,{\mathrm{<figure-callout\; id="1"\; label="D"\; filenames="HDA00001802076400021.png"\; state="\{\{state\}\}">D</figure-callout>}}_{1,i}^{-}+(-y_{i+1}-\frac{\mathrm{\&delta;}}{2})],$ Wherein, (i>=t+1),

And, based on the above embodiments, step 60 said with said statistics side-play amount with preset judge compare apart from threshold value, after generating pseudorange acceleration fault-signal, also comprise:

Step 70, judge to obtain according to the average of the average of said first data sequence and standard deviation, second data sequence and preset and be used to indicate the quality index average chain length value that detects performance apart from threshold value.

Obtain the average μ of first data sequence through each step in the foregoing description ₁And standard deviation sigma ₁, second data sequence average μ ₂Judge behind threshold value H with preset, further, can obtain quality index average chain length value ARL according to following computing formula, this quality index average chain length value ARL comprises the quality index average chain length value ARL that skew causes on the average ⁺With the quality index average chain length value ARL that squints and cause under the average ^-

$\frac{1}{\mathrm{APL}}=\frac{1}{{\mathrm{APL}}^{+}}+\frac{1}{{\mathrm{APL}}^{-}},$

${\mathrm{APL}}^{+}=\frac{\exp [-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)}{2{(\mathrm{\&delta;}-k)}^2},$

${\mathrm{APL}}^{-}=\frac{\exp [-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)]}{2{(-\mathrm{\&delta;}-k)}^2},$

Can obtain quality index average chain length value ARL according to above-mentioned formula:

$\frac{1}{\mathrm{APL}}=\frac{2{(\mathrm{\&delta;}-k)}^2}{\exp [-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)]}+\frac{{2(-\mathrm{\&delta;}-k)}^2}{\exp [-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)]}.$

In the aforementioned calculation formula;

k is the preset reference value; H judges apart from threshold value for preset; The value of k and H can be selected as required, and the k size can be

for

H size here

Certainly, present embodiment only provides a kind of method of obtaining quality index average chain length value, also can adopt existing additive method to obtain quality index average chain length value, and it is said to be not limited to present embodiment.

In the present embodiment; After the detection method generation pseudorange acceleration fault-signal through the foregoing description, further, obtain the quality index average chain length apart from threshold value according to the average and the preset judgement of first data sequence and second data sequence; The time size that the complete step 10 of this this detection method of quality index average chain length value representation to step 60 is required; Big I of this time is represented the detection performance of this detection method, and the time shorter (quality index average chain length value is more little) explains that the performance of this detection method is good more, that is to say that this detection method can detect pseudorange acceleration fault faster; In time find pseudorange acceleration fault; So that the staff in time adopts counter-measure, eliminate this fault, improve the navigation performance of satellite navigation Local Area Augmentation System.

One of ordinary skill in the art will appreciate that: all or part of step that realizes said method embodiment can be accomplished through comprising the relevant hardware of programmed instruction; Aforesaid program can be stored in the computer read/write memory medium; This program the step that comprises said method embodiment when carrying out; And aforesaid storage medium comprises: various media that can be program code stored such as ROM, RAM, magnetic disc or CD.

What should explain at last is: above each embodiment is only in order to explaining technical scheme of the present invention, but not to its restriction; Although the present invention has been carried out detailed explanation with reference to aforementioned each embodiment; Those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment put down in writing, perhaps to wherein part or all technical characteristic are equal to replacement; And these are revised or replacement, do not make the scope of the essence disengaging various embodiments of the present invention technical scheme of relevant art scheme.

Claims (6)

1. pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System is characterized in that, comprising:

The difference of the actual distance value at each collection moment ground monitoring station yard pseudo-range measurements and satellite and ground monitoring station is to obtain the data sequence of being made up of each said collection sign indicating number pseudo-range corrections value constantly in the said Preset Time section in the calculating Preset Time section;

To put the seclected time in the said Preset Time section is that cut-point is divided into first data sequence and second data sequence with said data sequence;

Said first data sequence and second data sequence are carried out statistical treatment, obtain the average and the standard deviation of said first data sequence and second data sequence;

Average and standard deviation according to said first data sequence and second data sequence are obtained the sequential probability that breaks down;

Said sequential probability that breaks down and preset threshold value out of control are compared, obtain the side-play amount statistical value;

Know said side-play amount statistical value when judgement and when judging, generate pseudorange acceleration fault-signal apart from threshold value greater than preset.

2. pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System according to claim 1 is characterized in that:

Saidly said first data sequence and second data sequence carried out statistical treatment comprise with average and the standard deviation of obtaining said first data sequence and second data sequence:

According to

Obtain the average μ of said first data sequence ₁

According to

Obtain the standard deviation sigma of said first data sequence ₁

According to

Obtain the average μ of said second data sequence ₂

According to

Obtain the standard deviation sigma of said second data sequence ₂

Wherein, t representes the time point in the said Preset Time section, and m representes the end time of said Preset Time section, PRctS _iRepresent that i gathers sign indicating number pseudo-range corrections value constantly.

3. pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System according to claim 2 is characterized in that:

The said sequential probability value that breaks down according to the average and the standard deviation calculating of said first data sequence and second data sequence comprises:

According to $P={\left(\frac{1}{\mathrm{\&alpha;}}\right)}^{m-t}\mathrm{Exp}[-\frac{1}{{2\mathrm{\&alpha;}}^2}\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}{(y_i-\mathrm{\&delta;})}^2+\frac{1}{2}\underset{i=t+1}{\overset{m}{\mathrm{\&Sigma;}}}{y_i}^2]$ Obtain the sequential probability value P that breaks down, wherein, $\mathrm{\&alpha;}=\sqrt{\frac{{\mathrm{\&sigma;}}_2}{{\mathrm{\&sigma;}}_1}},$ $\mathrm{\&delta;}=\frac{{\mathrm{\&mu;}}_2-{\mathrm{\&mu;}}_1}{{\mathrm{\&sigma;}}_1},$ $y_i=\frac{\mathrm{PRct}{S}_i-{\mathrm{\&mu;}}_1}{{\mathrm{\&sigma;}}_1}.$

4. pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System according to claim 3 is characterized in that:

Said said sequential probability that breaks down and preset threshold value out of control are compared, obtain the side-play amount statistical value and comprise:

When said sequential probability value P is known in judgement greater than preset threshold value out of control; Obtain side-play amount statistical value or

wherein through or

; I>=t+1,

5. according to pseudorange acceleration fault detection method in the arbitrary described satellite navigation Local Area Augmentation System of claim 1-4, it is characterized in that:

Said with said statistics side-play amount with preset judge compare apart from threshold value, after generating pseudorange acceleration fault-signal, also comprise:

Judge to obtain according to the average of the average of said first data sequence and standard deviation, second data sequence and preset and be used to indicate the quality index average chain length value that detects performance apart from threshold value.

6. pseudorange acceleration fault detection method in the satellite navigation Local Area Augmentation System according to claim 5 is characterized in that:

The average of said average and standard deviation, second data sequence according to said first data sequence and preset is judged to obtain apart from threshold value and is used to indicate the quality index average chain length value that detects performance to comprise:

According to $\frac{1}{\mathrm{APL}}=\frac{2{(\mathrm{\&delta;}-k)}^2}{\mathrm{Exp}[-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)]}+\frac{{2(-\mathrm{\&delta;}-k)}^2}{\mathrm{Exp}[-2(\mathrm{\&delta;}-k)(H+1.166)+2(\mathrm{\&delta;}-k)(H+1.66)]}$ Obtain the quality index average chain length value ARL that is used to indicate the detection performance, wherein, K is the preset reference value, and H judges apart from threshold value for preset.

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