A geophysical field matching navigation adaptability analysis method based on bias estimation

Abstract

The present disclosure provides a geophysical field matching navigation adaptability analysis method based on bias estimation. First, node division is performed within the adaptability analysis window; the geophysical field characteristic value of each node is determined according to the geophysical field background map; the longitude matching bias model and the latitude matching bias model of the geophysical field matching are determined respectively according to the prior probability distribution type of the true position and the matching algorithm to be used, and then the estimated longitude and latitude overall matching bias is obtained by substituting the prior probability distribution parameters and the geophysical field characteristic value of each node; the estimated longitude overall matching bias is used to measure the longitude adaptability of the geophysical field matching navigation, the estimated latitude overall matching bias is used to measure the latitude adaptability of the geophysical field matching navigation, and the adaptability analysis is realized. Using the present application can quantitatively measure the adaptability of the geophysical field matching navigation with the estimated matching bias, and the adaptability of longitude and latitude can be distinguished.

Description

Technical Field

[0001] The present invention relates to the field of navigation, guidance and control technology, and in particular to a geophysical field matching navigation adaptability analysis method based on deviation estimation. Background Art

[0002] Navigation technology is one of the key technologies for sea, land and air navigation. It directly determines whether the vehicle can navigate safely and accurately reach the designated operating location. It is a key factor in determining the success or failure of the mission.

[0003] Inertial navigation systems offer the advantages of autonomy and stealth, enabling high-precision navigation in a short period of time. They are one of the most important navigation methods and are often used as the primary navigation and positioning system in integrated navigation. However, navigation errors accumulate over time, making them prone to significant positioning errors during extended operation. Therefore, long-duration navigation requires correction using other navigation sensors or systems.

[0004] The basic principle of geophysical matching navigation (GMP) is to compare a precisely pre-acquired geophysical background image with the geophysical field characteristics of the vehicle's location, continuously measured by sensors, to determine the vehicle's position. GMP can be divided into terrain matching navigation, gravity matching navigation, and geomagnetic matching navigation, depending on the geophysical parameters.

[0005] Compatibility analysis is the foundation of geophysical matching navigation. However, matching in feature-deficient and poorly compatible areas can lead to significant errors. Traditional compatibility analysis is often based on characteristic statistical parameters, making thresholds difficult to determine. Most approaches can only qualitatively describe the quality of the matching, but cannot quantitatively analyze matching deviation (matching accuracy) or provide analytical formulas for matching deviation (matching accuracy). Furthermore, traditional methods often consider compatibility as a characteristic of the geophysical background map itself, rather than the capabilities of the system, including search windows, observation accuracy, geophysical background maps, and matching algorithms. This makes it impossible to comprehensively and accurately assess the quality of the matching. Furthermore, while traditional methods can represent differences in latitude and longitude characteristics to a certain extent, they cannot clearly distinguish between matching areas in latitude and longitude. Summary of the Invention

[0006] In view of this, the present invention provides a geophysical field matching navigation adaptability analysis method based on deviation estimation, which can quantitatively measure the adaptability of geophysical field matching navigation using the estimated matching deviation, and can also distinguish the adaptability of each latitude and longitude.

[0007] In order to solve the above technical problems, the present invention is implemented as follows.

[0008] A geophysical field matching navigation adaptability analysis method based on deviation estimation, the method comprising:

[0009] Step 1: In the given adaptability analysis window S ear Perform node division inside to obtain i×j nodes;

[0010] Step 2: Input the geophysical field background map and determine the geophysical field characteristic value of each node;

[0011] Step 3: Determine the longitude matching deviation model and the latitude matching deviation model for geophysical field matching based on the prior probability distribution type of the real position and the matching algorithm to be used;

[0012] Step 4: Substitute the distribution parameters corresponding to the prior probability distribution type and the geophysical field characteristic values ​​of each node into the model determined in step 3 to obtain the estimated longitude overall matching deviation β x and the overall matching deviation β of latitude y ;

[0013] Step 5: Use the estimated longitude overall matching deviation β x To measure the longitude adaptability of geophysical field matching navigation, the estimated latitude overall matching deviation β is used. y Measure the latitude adaptability of geophysical field matching navigation and implement adaptability analysis.

[0014] Preferably, in step 3, according to the prior probability distribution type of the real position and the matching algorithm to be used, the overall longitude matching deviation model and the overall latitude matching deviation model of the geophysical field matching are respectively determined as follows:

[0015] Step 31: Using the position of the spacecraft as an estimate;

[0016] Step 32: Determine the prior probability distribution of the position based on the prior conditions;

[0017] Step 33: The observation results of the geophysical field characteristic values ​​are determined by the geophysical field characteristics at the spacecraft's location and are affected by observation errors. Based on the characteristics of the observation errors and the geophysical field background map, the conditional probability distribution of the geophysical field characteristic value observations with respect to the spacecraft's location is obtained.

[0018] Step 34: Assume the true position of a spacecraft as condition 1, and obtain an estimate of the posterior probability distribution of the spacecraft position under condition 1 based on the conditional probability distribution of the spacecraft position based on the geophysical field eigenvalue observations, the selected matching algorithm, and the observation error characteristics;

[0019] Step 35: Based on the posterior probability distribution estimate of the aircraft position under condition 1 in step 34, obtain an estimated value of the position under condition 1; compare it with the assumed true position and calculate the matching deviation of the estimate under condition 1;

[0020] Step 36: Since the estimated matching deviation obtained in step 35 is based on a certain assumed real position, all possible real positions are traversed, and steps 34-35 are repeated. Combined with the prior probability distribution of the real position, an estimate of the overall matching deviation within the search range is obtained.

[0021] Preferably, the matching algorithm is based on Bayesian estimation.

[0022] Preferably, the prior probability distribution type is the adaptability analysis window S ear The uniform distribution within the geophysical field is σ, and the observation standard deviation of the geophysical field characteristic value is σ; the matching algorithm adopts particle filtering or its derivative algorithm; then the overall longitude matching deviation model and the overall latitude matching deviation model of the geophysical field matching are:

[0023]

[0024] Among them, β x is the adaptability analysis window S ear The overall matching bias estimate for longitude within β y is the adaptability analysis window S ear The overall matching deviation estimate for latitudes within , is the adaptability analysis window S ear Any node within The characteristic value of the geophysical field at is the adaptability analysis window S ear Any node within The geophysical field characteristic value at node is the adaptability analysis window S ear The possible real positions within need to be traversed. is a node The characteristic values ​​of the geophysical field at .

[0025] Preferably, the range of particle filtering is used as the adaptability analysis window S ear .

[0026] Preferably, for the overall matching deviation β x and the overall matching deviation β of latitude y Criteria are set separately, and suitability analysis of longitude and latitude is performed based on the criteria.

[0027] Preferably, in step 5, the overall matching deviation β of the longitude x and the overall matching deviation β of latitude y Perform fusion calculations and conduct overall adaptability analysis of the nodes based on the fusion results.

[0028] Preferably, the geophysical field is a gravity field, a geomagnetic field or a topography.

[0029] Beneficial effects:

[0030] (1) The present invention provides a geophysical field matching navigation adaptability analysis method based on deviation estimation. It uses the knowledge of probability theory and calculus to quantitatively estimate the matching deviation of geophysical field matching navigation, and uses the matching deviation to measure the adaptability, so that the matching effect can be quantified and has a clear physical meaning, which is convenient for threshold setting. It overcomes the shortcomings of traditional methods that the threshold is difficult to determine and cannot quantitatively describe the matching effect.

[0031] (2) When quantifying adaptability, the present invention regards it as the ability of the system that is related to the search area, observation accuracy (standard deviation σ), geophysical field background map, and matching algorithm, rather than just the characteristics of the geophysical field background map. This can more comprehensively and accurately measure the matching effect.

[0032] (3) The present invention can independently estimate the adaptability of longitude and latitude, and more fully explore the matching area.

[0033] (4) In a preferred embodiment, the range of the particle filter is used as the window for the adaptability analysis. The adaptability analysis window and the range of the particle filter are consistent. There will be no adaptability estimation error due to inconsistent window ranges, and the adaptability analysis will be more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of a method for analyzing the adaptability of geophysical field matching navigation based on deviation estimation provided by the present invention. DETAILED DESCRIPTION

[0035] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0036] Since underwater gravity matching navigation is an important underwater passive navigation method and the gravity field information is stable, the present invention is described using underwater gravity matching navigation. However, the present invention is also applicable to other geophysical field matching navigation methods such as terrain matching navigation and geomagnetic matching navigation, and is also applicable to non-underwater scenarios such as land and aviation. Figure 1 A flowchart of a method for analyzing the suitability of geophysical field matching navigation based on deviation estimation provided by the present invention is provided. This method quantifies the suitability of geophysical field matching navigation by estimating the longitude and latitude matching deviation. The process is as follows:

[0037] Step 1: Use the range of particle filtering as the window S for adaptability analysis ear According to the accuracy and computational complexity, choose the appropriate latitude and longitude step size. earThe advantage is that the window of the adaptability analysis is consistent with the range of the particle filter, which will not cause adaptability estimation errors due to inconsistent window ranges, and the adaptability analysis is more accurate.

[0038] Step 2: Using gravity anomalies as observations, assuming the overall observation error is Gaussian with a standard deviation of σ, input the gravity anomaly background map and the value of σ to determine the geophysical field characteristic values ​​for each node. This approach has the advantage of considering the impact of gravity anomaly observation noise on adaptability and performing quantitative calculations.

[0039] Step 3: According to the prior probability distribution type of the real position and the matching algorithm to be used, the longitude matching deviation model and the latitude matching deviation model of the geophysical field matching are determined respectively.

[0040] The matching algorithm selected in this embodiment is particle filtering or its derivative algorithm, and it is assumed that the prior probability distribution of the real position is S ear The latitude and longitude matching deviation of gravity matching navigation is estimated by the following formula:

[0041]

[0042] Among them, β x For S ear The overall matching bias estimate for longitude within β y For S ear The overall matching deviation estimate for latitudes within , For S ear Any node within The sampling value of the gravity anomaly background map at For S ear Any node within Gravity anomaly background map sampling value at node It's S ear The possible real positions within the need to be traversed; is a node The advantage of this method is that it provides the theoretical positioning deviation of gravity matching navigation based on particle filter algorithm.

[0043] Step 4: Substitute the distribution parameters corresponding to the prior probability distribution type and the geophysical field characteristic values ​​of each node into the model determined in step 3 to obtain the estimated longitude overall matching deviation β x and the overall matching deviation β of latitude y .

[0044] Step 5: Use the estimated β x and β yThey are respectively used as quantitative indicators of the latitude and longitude adaptability of gravity matching navigation. Its advantage is that the adaptability can be quantified and the physical meaning (matching deviation) is clear; and because β x and β y They can be calculated separately, the adaptability of longitude and latitude can be distinguished, and criteria can be set separately, such as adaptation criteria based on thresholds, so that they can better adapt to the directional differences of the gravity field and fully explore the matching areas.

[0045] In practice, it is also possible to match the estimated longitude with an overall deviation β x and the overall matching deviation β of latitude y Perform fusion calculations and conduct overall adaptability analysis on the corresponding nodes based on the fusion results.

[0046] The following gives β x and β y The derivation process:

[0047] Assume that the measured value of gravity anomaly is g me , easy to know, g me is a random variable, denoted as G. Assume that the node is the true position, and the probability density function of G is represents a normal distribution with a standard deviation of σ and an expectation of Indicates that when gravity anomaly observation is performed, the node exist is the observation weight under the assumption of the true position, denoted as random variable P1. It is recorded as P1=g(G), where g represents the functional relationship between P1 and G. The probability density function of P1 is E(P1) represents the node exist is the weight expectation under the assumption of the true position. Since the inverse function of function g does not necessarily exist, The expression of cannot be obtained directly, so it is necessary to find an equivalent form of the integral. Since g is not necessarily a monotonic function, without loss of generality, assume that the interval {g(G)|y≤g(G)<y+dy} on the range of function P1=g(G) corresponds to the interval {G|x1≤G<x1+dx1}∪{G|x2≤G<x2+dx2}∪......∪{G|x n ≤G<x n +dx n},{G|x1≤G<x1+dx1},…,{G|x n ≤G<x n +dx n} and so on. Each subinterval does not intersect with each other. There is P(y≤g(G)<y+dy)=f G (x1)dx1+f G (x2)dx2+……+f G (x n )dx n .

[0048] And because y=g(x1)=g(x2)=……=g(x n ), so yf P1 (y)dy=g(x1)f G (x1)dx1+g(x2)f G (x2)dx2+…+g(x n )f G (x n )dx n From the meaning of differential and integral, we can know that Right now because Arbitrary, Respectively expressed in is the estimate of the longitude and latitude matching deviation under the assumption of the true position. It may be any position within the window, assuming that the prior probability distribution of the true position is S ear The uniform distribution within

[0049]

[0050] Among them, β x For S ear The overall matching bias estimate for longitude within β y For S ear The overall matching bias estimate for latitude within .

[0051] Although only gravity anomalies are observed here, and the prior probability distribution of the true position is assumed to be S ear If other observations are added or the prior probability distribution of the true position is changed, the formula can be deformed according to the principle of formula derivation. The principle of formula derivation is summarized as follows:

[0052] Step (1) uses the position of the aircraft as an estimate;

[0053] Step (2) determining the prior probability distribution of the position according to the prior conditions;

[0054] Step (3) The observation results of the geophysical field characteristic values ​​are determined by the geophysical field characteristics at the position of the spacecraft and are affected by the observation error. Based on the characteristics of the observation error and the geophysical field background map, the conditional probability distribution of the geophysical field characteristic value observations with respect to the spacecraft position is obtained;

[0055] Step (4) assumes the true position of a spacecraft (denoted as condition 1), and obtains an estimate of the posterior probability distribution of the spacecraft position under condition 1 based on the conditional probability distribution of the spacecraft position from the geophysical field eigenvalue observations, the selected matching algorithm (essentially estimating the selected model), and the observation error characteristics;

[0056] Step (5) estimates the posterior probability distribution of the aircraft position under condition 1 in step (4) to obtain an estimated value of the position under condition 1. Compare it with the assumed true position and calculate the matching deviation of the estimate under condition 1;

[0057] Step (6) Since the estimated matching deviation obtained in step (5) is based on a certain assumed real position, all possible real positions are traversed, and steps (4) to (5) are repeated. Combined with the prior probability distribution of the real position, an estimate of the overall matching deviation within the search range is obtained.

[0058] The above specific embodiments merely illustrate the design principles of the present invention. The shapes and names of the components described herein may vary and are not limiting. Therefore, those skilled in the art may modify or substitute equivalents for the technical solutions described in the above embodiments. Such modifications and substitutions, without departing from the inventive spirit and technical solutions of the present invention, shall fall within the scope of protection of the present invention.

Claims

1. A geophysical field matching navigation adaptability analysis method based on deviation estimation, characterized in that: The method includes: Step 1: In the given adaptability analysis window S ear Perform node division inside to obtain i×j nodes; Step 2: Input the geophysical field background map and determine the geophysical field characteristic value of each node; Step 3: Determine the overall longitude matching deviation model and the overall latitude matching deviation model for geophysical field matching based on the prior probability distribution type of the real position and the matching algorithm to be used; The prior probability distribution type is the adaptability analysis window S ear The uniform distribution within the geophysical field is σ, and the observation standard deviation of the characteristic value of the geophysical field is σ; the matching algorithm adopts particle filtering or its derivative algorithm; then the overall longitude matching deviation model and the overall latitude matching deviation model of the geophysical field matching are: Among them, β x is the adaptability analysis window S ear The overall matching bias estimate for longitude within β y is the adaptability analysis window S ear The overall matching deviation estimate for latitudes within , is the adaptability analysis window S ear Any node within The characteristic value of the geophysical field at is the adaptability analysis window S ear Any node within The geophysical field characteristic value at node is the adaptability analysis window S ear The possible real positions within need to be traversed. is a node The characteristic value of the geophysical field at ; Step 4: Substitute the distribution parameters corresponding to the prior probability distribution type and the geophysical field characteristic values ​​of each node into the model determined in step 3 to obtain the estimated longitude overall matching deviation β x and the overall matching deviation β of latitude y ; Step 5: Use the estimated longitude overall matching deviation β x To measure the longitude adaptability of geophysical field matching navigation, the estimated latitude overall matching deviation β is used. y Measure the latitude adaptability of geophysical field matching navigation and implement adaptability analysis.

2. The method for analyzing the suitability of geophysical field matching navigation based on deviation estimation according to claim 1, characterized in that: The range of particle filtering is used as the adaptability analysis window S ear .

3. The method for analyzing the suitability of geophysical field matching navigation based on deviation estimation according to claim 1, characterized in that: Overall matching deviation β for longitude x and the overall matching deviation β of latitude y Criteria are set separately, and suitability analysis of longitude and latitude is performed based on the criteria.

4. The method for analyzing the suitability of geophysical field matching navigation based on deviation estimation according to claim 1, wherein: In step 5, the overall matching deviation β of longitude x and the overall matching deviation β of latitude y Perform fusion calculations and conduct overall adaptability analysis of the nodes based on the fusion results.

5. The method for analyzing the suitability of geophysical field matching navigation based on deviation estimation according to claim 1, characterized in that: The geophysical field is a gravity field, a geomagnetic field or a topography.

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