CN104776845B - Autonomous star recognition method based on combination mode - Google Patents

Abstract

The invention discloses a main star identification method based on a combination mode, which adopts the characteristics of the combined main star in the combination mode of the radial mode and the coding mode as the feature vector of the main star; The search range in the navigation star feature library matches and compares the feature vector of the main star with the vector in the navigation star feature library to complete the autonomous identification of the star. The combination mode of the main star in the present invention has the invariance of translation and rotation, and has a higher recognition rate, making it more suitable for the independent recognition of stars; meanwhile, it has a faster star recognition speed, which is beneficial to improving the sensitivity of the system.

Description

A Method of Autonomous Satellite Identification Based on Combination Patterns

technical field

The invention belongs to the technical field of navigation, and in particular relates to an autonomous star identification method based on a combined pattern.

Background technique

In celestial navigation and positioning, the positioning and identification of stars in the sky can effectively determine the direction information of the aircraft; based on scientific research and hardware cost considerations, the autonomous star tracker is regarded as the first choice for attitude measurement equipment on most aircraft; An autonomous star tracker can automatically identify stars and calculate the attitude of the aircraft; the accuracy of star identification directly affects the accuracy of the attitude of the aircraft. Therefore, in the star sensor, effective and accurate star identification algorithm is very critical.

In the past few decades, many scholars have devoted themselves to the research of star recognition algorithm, and the star tracker based on this basis has been widely used in the attitude calculation and control of aircraft; the star recognition algorithm can be divided into two basic categories: subgraph Isomorphism and pattern recognition; in these algorithms, no prior information about the attitude of the vehicle is utilized; in the first classification, star points are used as vertices of the graph, using the planar distance between star pairs, or the distance between three stars The plane distance (may also include the brightness information of the star point) is used as the feature of star recognition. This type of algorithm mainly includes triangle algorithm, polygon algorithm and group matching algorithm, etc.; Some observation stars or all observation stars are used to construct an easy-to-define pattern, and its representative algorithms include grid algorithm, neural network algorithm and genetic algorithm.

In recent years, due to the development of pattern recognition, it has been widely used in star recognition. Zhang Guangjun et al. proposed an all-sky autonomous satellite identification algorithm based on the radial and circular characteristics of star patterns. Compared with the grid algorithm, this algorithm has more robust identification performance. In this algorithm, the radial mode has reliable rotation invariant characteristics. However, the algorithm relies on the size of the storage space and the overhead of recognition time to obtain better performance; at the same time, the cyclic feature is sensitive to position noise. In order to reduce the complexity of the star recognition algorithm and speed up the star recognition, Youngwoo Yoon proposed The idea of encoding patterns reduces the pattern matching problem to a comparison between integer values. However, this algorithm needs to select a suitable neighboring star to construct the base axis of the star pattern. The probability of selecting a suitable neighboring star is often relatively low. Therefore, if an unsuitable neighboring star is selected, a wrong base axis will be generated, which will lead to unsuccessful star identification. In addition, other scholars have proposed different star recognition algorithms on the basis of pattern recognition.

In the star sensor, it is required to realize star identification as quickly and reliably as possible, so as to improve more accurate identification information for subsequent processing. With the development of deep space exploration, the requirements for star recognition algorithms are getting higher and higher. Therefore, it is of great significance to establish a fast, accurate and robust star recognition algorithm.

Contents of the invention

The purpose of the present invention is to provide an autonomous star recognition method based on combined patterns, aiming at solving the problems of low recognition rate and slow recognition speed of existing star recognition algorithms.

The present invention is realized in this way, a kind of main star identification method based on combination mode, this main star identification method based on combination mode divides the neighborhood range of main star into equidistant ring belts from inside to outside, main star and each ring belt The average planar distance of the adjacent stars on the above constitutes the characteristics of the main star in the radial mode; the number of adjacent stars on each ring, and the encoding value obtained by using the encoding base are the characteristics of the main star in the encoding mode; the combined main star in the radial mode The features in mode and encoding mode constitute the feature vector of the main star in the combination mode; point the optical axis of the CCD to the navigation stars in the basic star catalog one by one, generate the feature vector corresponding to the navigation star, and save it in the form of a database to form a navigation star feature library; use the code value corresponding to the main star to narrow the search range in the navigation star feature library, match and compare the feature vector of the main star with the vector in the navigation star feature library, and calculate the feature vector of the main star and the navigation star feature The similarity of the vectors in the library, so as to obtain the recognition result.

Further, before obtaining the eigenvector of the main star in the combination mode, it is necessary to:

Calculate the coordinates of the navigation star in the star map image: calculate the coordinates of the navigation star in the star map image according to the coordinates of the navigation star in the inertial coordinate system and according to certain conversion rules;

Determine the star mode of the main star: take an observed star in the field of view as the main star, and determine the neighboring stars of the main star according to the size of the neighborhood radius, and the star mode of the main star is composed of the main star and the neighboring stars.

Further, the conversion formula of the coordinates of the navigation star in the inertial coordinate system to the coordinates in the star map image is as follows:

Among them, (N _x , N _y ) is the resolution of the CCD in the star sensor, (FOV _x , FOV _y ) is the size of the field of view of the CCD, (α _i , δ _i ) are the right ascension and declination of the observed star, respectively, (α, δ) is the direction of the optical axis of the CCD; the optical axis of the CCD always points to the position of the navigation star in the inertial coordinates, and the navigation star is projected to the center of the star map image.

Further, select the observation star in the center of the field of view or close to the center of the field of view as the main star, in order to obtain the complete star pattern of the main star; according to the size of the neighborhood and the position of the main star, determine the position information of the main star’s neighboring star, and the main star and the neighboring star The position information of constitutes the star pattern of the main star.

Further, the characteristics of the main star in the radial mode: the neighborhood of the main star is divided into n rings on average along the radial direction of the main star, and the average plane distance between the adjacent star and the main star on each ring is counted, and n rings are used The mean in-plane distance along the belt is used to characterize the host star in the radial pattern.

Further, the specific method of the average plane distance between the neighboring star and the main star on each ring is:

The n rings are marked as C0, C1, ..., Cn-1 from the inside to the outside, and the radius of the neighborhood of the main star is R, then the inner boundary of the i-th (i=0,...,n-1) ring and The outer boundaries are respectively expressed as i*R/n and (i+1)*R/n, and the coordinates of the neighboring star on the i-th ring should meet the following conditions:

i=0,...,n-1;

Among them, (x0, y0) and (x, y) are the coordinates of the center of mass of the main star and the neighboring star on the star map image respectively, and n is the number of rings in which the main star neighborhood is equally divided;

The number of neighboring stars on each ring is expressed as Ni (i=0,...,n-1), and the average plane distance between the main star and the neighboring star on the i-th ring is expressed as:

i=0,...n-1;

Among them, (xij, yij) is the barycenter coordinates of the jth neighboring star on the i-th ring on the star map image, Ni is the number of neighboring stars on the i-th ring, and the average plane of n rings The distance constitutes the characteristic of the host star in the radial mode, which is expressed as:

D_vector={D ₀ ,D ₁ ,...,D _n-1 };

Further, the characteristics of the main star in the encoding mode: count the number of neighboring stars in each ring, use the preset encoding base, and encode according to certain encoding rules, and the obtained encoding value is used as the feature of the main star in the encoding mode.

Further, the method to obtain the encoded value is:

The number of adjacent stars on the i-th ring is N _i (i=1,...,n), then the corresponding encoding value of the main star in the encoding mode is expressed as:

Where b is the encoding base.

Further, the eigenvector of the main star in the combination mode is expressed as:

Vector = {V _s , D_vector};

In the navigation star feature database, the record corresponding to each navigation star is expressed as:

Record={id,Vector}={id,V _s ,D_vector};

Among them, id is the label of the navigation star, V _s is the code value corresponding to the navigation star, that is, the feature of the navigation star as the main star in the encoding mode, D_vector is the navigation star as the main star and the adjacent stars on n rings in its neighborhood Characterization of host stars in radial mode by mean planar distance.

Further, the process of main star identification is expressed as:

result=min{diff{Vector _s ,Vector _c }},V _s ∈Vector _s ,V _c ∈Vector _c ,V _c ∈[V _s -ε ₁ ,V _s -ε ₂ ];

Among them, V _s is the encoding value in the feature vector corresponding to the navigation star s, V _c is the encoding value in the feature vector corresponding to the navigation star c in the feature library, ε ₁ and ε ₂ are the allowable errors of the encoding value .

In the autonomous star identification method based on the combination mode provided by the present invention, the eigenvector of the navigation star characterizes the characteristics of the navigation star in the radial mode and the encoding mode, has translation and rotation invariance, and is suitable for the identification of the autonomous star in the star sensor. In the star recognition process, there is no need to search the entire navigation star feature library, and the recognition results can be obtained quickly. The star recognition process is simplified to a single comparison between feature vectors.

The beneficial effects of the present invention are:

1. The features in the radial mode have translation invariance, and the features in the coding mode have rotation invariance. Based on the features in the combination mode, the advantages of the radial mode and the coding mode are combined, which is suitable for star recognition in complex environments;

2. Use the code value corresponding to the main star to limit the search range, improve the speed of star recognition, and enhance the sensitivity of the system;

3. The star recognition method based on combination mode is simple and easy to operate, which simplifies the process of star recognition and provides a new idea for star recognition;

4. The autonomous star recognition method based on the combination mode provided by the present invention is better than the existing pyramid star recognition method and the star recognition algorithm based on the improved grid under the same conditions as the prior art;

5. The simple, fast and stable star recognition method based on the combination mode of the present invention can provide more accurate recognition information for aircraft attitude calculation and navigation positioning.

Description of drawings

Fig. 1 is the flow chart of the autonomous satellite identification method based on combination mode provided by the embodiment of the present invention;

Fig. 2 is an imaging schematic diagram of a star projected from an inertial coordinate system to a star map image plane coordinate system in a star sensor provided by an embodiment of the present invention;

Fig. 3 is the annulus of the main star neighborhood division provided by the embodiment of the present invention;

Fig. 4 is a schematic diagram of the result of the navigation star feature library provided by the embodiment of the present invention.

detailed description

In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

The application principle of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

As shown in Figure 1, the autonomous satellite identification method based on the combined pattern of the embodiment of the present invention comprises the following steps:

S101: Calculate the coordinates of the navigation star in the star map image: calculate the coordinates of the navigation star in the star map image according to the coordinates of the navigation star in the inertial coordinate system and according to certain conversion rules;

S102: Determine the star mode of the main star: take an observed star in the field of view as the main star, determine the neighboring star of the main star according to the size of the neighborhood radius, and the star mode of the main star is composed of the main star and its neighboring stars;

S103: Extract the characteristics of the main star in the radial mode: divide the neighborhood of the main star into n rings on average along the radial direction of the main star, and count the average plane distance between the neighboring star and the main star on each ring, using n The mean plane distance on the ring is used as the characteristic of the host star in the radial mode;

S104: Extract the characteristics of the main star in the encoding mode: count the number of neighboring stars on each ring, use the preset encoding base, encode according to certain encoding rules, and use the obtained encoding value as the feature of the main star in the encoding mode ;

S105: Establish the eigenvector of the main star: according to the characteristics of the main star in the radial mode and the encoding mode, obtain the eigenvector of the main star in the combined mode;

S106: Generate a feature database of the navigation star: point the optical axis of the CCD to the navigation star in the basic star catalog one by one, generate a feature vector corresponding to the navigation star, and save it in the form of a database;

S107: Determine the result of star recognition: according to the characteristics of the navigation star feature vector, use the code value corresponding to the main star to limit its search range in the navigation star feature library, and calculate the similarity between the feature vector of the main star and the vector in the navigation star feature library degree, so as to obtain the recognition result.

In step S101, the navigation star is selected from the basic stellar database according to certain rules; the Tycho 2 star catalog is used as the basic stellar database; in the star catalog, some stars lack brightness information, and some stars lack position information , none of these stars can be used as a navigation star; due to the limitation of the CCD resolution in the star sensor, when the two stars are relatively close to each other, they cannot be clearly distinguished; when the distance between the two stars is less than 20 pixel (about 0.39°), it is regarded as a double star; the double star cannot be used as a navigation star; therefore, in the Tycho 2 star catalog, there are 6685 stars that can be used as a navigation star, and its magnitude ranges from 1.0mv to 6.5 mv; The coordinates of the navigation star in the inertial coordinate system are obtained from the basic star database, so the position information of the navigation star constitutes the basic database of the navigation star.

In step S101, the conversion formula of the coordinate conversion of the navigation star in the inertial coordinate system to the coordinates in the star map image is as follows:

Among them, (N _x , N _y ) is the resolution of the CCD in the star sensor, (FOV _x , FOV _y ) is the size of the field of view of the CCD, (α _i , δ _i ) are the right ascension and declination of the observed star, respectively, (α, δ) is the direction of the optical axis of the CCD; the optical axis of the CCD always points to the position of the navigation star in the inertial coordinates, and the navigation star is projected to the center of the star map image.

In step S102, due to the limitation of the size of the field of view of the CCD, some neighboring stars are missing from the observed stars located at the edge of the field of view, resulting in the loss of a large amount of geometric information of the star pattern, so the corresponding star pattern is incomplete; The observed star in the center of the field or close to the center of the field of view is used as the main star in order to obtain the complete star pattern of the main star; according to the size of the neighborhood and the position of the main star, the position information of the neighboring star of the main star is determined, and the position information of the main star and its neighboring star is determined. The star pattern that makes up the primary star.

In step S103, a circular area with a certain radius around the main star is the neighborhood of the main star, and the neighborhood of the main star is divided into n rings on average along the radial direction of the main star, and the neighboring stars in the neighborhood only belong to a certain ring, According to the position information of the main star and its neighboring star on the star map image, calculate the average plane distance between the neighboring star and the main star in each ring; the specific method is:

Assuming that n rings are marked as C0, C1, ..., Cn-1 from inside to outside, and the radius of the neighborhood of the main star is R, then the inner boundary of the i-th (i=0,...,n-1) ring and the outer boundary are expressed as i*R/n and (i+1)*R/n respectively; therefore, the coordinates of the neighboring star on the i-th ring should satisfy the following conditions:

i=0,...,n-1;

Among them, (x0, y0) and (x, y) are the coordinates of the center of mass of the main star and the neighboring star on the star map image respectively, and n is the number of rings in which the main star neighborhood is equally divided;

Assuming that the number of neighboring stars on each ring is represented as Ni (i=0,...,n-1), the average plane distance between the main star and the neighboring star on the i-th ring can be expressed as:

i=0,...n-1

Among them, (xij, yij) is the barycenter coordinates of the jth neighbor star on the i-th ring on the star map image, and Ni is the number of neighboring stars on the i-th ring.

In step S104, count the number of adjacent stars on each ring, use the preset coding base, encode according to certain coding rules, and obtain the coded value as the characteristic of the main star in the coding mode; The number of adjacent stars of is N _i (i=1,...,n), then the code value corresponding to the main star in the coding mode can be expressed as:

Where b is the encoding base.

In step S105, combining the advantages of the radial mode and the encoding mode, the average plane distance between the main star and the neighboring stars on each ring is used to describe the characteristics of the main star in the radial mode, and the encoding value is used to describe the characteristics of the main star in the encoding mode. Features, the eigenvector of the main star is represented by the features of the main star in the combination mode of the radial mode and the coding mode, so the eigenvector of the main star in the combination mode can be expressed as:

Vector={V _s , D ₀ , D ₁ , . . . , D _n+1 }={V _s , D_vector}.

In step S106, the feature database stores the corresponding eigenvector information of all navigation stars; the CCD in the star sensor points to the selected navigation star one by one, and obtains the positions of the observation stars distributed in the field of view on the star map image, according to the eigenvector According to the generation rules of the main star, the eigenvector corresponding to the main star is obtained and stored in the navigation star feature library; the vector in the navigation star feature library is the eigenvector corresponding to the observation star as the main star without any noise; from the above According to the description of , in the navigation star feature database, the record corresponding to each navigation star can be expressed as:

Record＝{id,Vector}＝{id,V _s ,D_vector}

Among them, id is the label of the navigation star, V _s is the code value corresponding to the navigation star, that is, the feature of the navigation star as the main star in the encoding mode, and D_vector is the navigation star as the main star and the adjacent stars on n rings in its neighborhood The characteristics of the host star in the radial mode formed by the mean planar distance of .

The star recognition process described in step S107 is for any star map image, select a certain observation star on the star map image as the main star, construct the characteristics of the main star in radial mode and encoding mode, and use the corresponding The coded value of the guide star limits its search range in the navigation star feature library, calculates the similarity between the feature vector of the main star and the vector in the navigation star feature library, and determines whether the two feature vectors are consistent or similar, so as to determine whether the observed star is the corresponding one. The navigation star, so as to get the recognition result.

In step S107 , defining the search range in the navigation star feature library during star identification is to use the code value corresponding to the main star to limit its search range in the navigation star feature library. Due to the influence of noise or other interference factors, there is a certain difference between the code value corresponding to the observation star as the main star and the code value corresponding to the same observation star as the main star without any noise. When identifying stars, only the navigation stars corresponding to the coded values within a certain difference range in the feature library are allowed to be matched and identified. Within the limited search range, a small number of comparisons can be used to quickly obtain the recognition results without searching the entire navigation star Feature Library. The process of star recognition can be expressed as:

result＝min{diff{Vector _s ,Vector _c }},V _s ∈Vector _s ,V _c ∈Vector _c ,V _c ∈[V _s -ε ₁ ,V _s -ε ₂ ]

Among them, V _s is the encoding value in the feature vector corresponding to the navigation star s, V _c is the encoding value in the feature vector corresponding to the navigation star c in the feature library, ε ₁ and ε ₂ are the allowable errors of the encoding value .

As shown in Figure 2, the navigation star uses coordinates on the x-axis and y-axis in the star map image to represent its position on the image plane; the navigation star is selected from the basic star list according to certain rules, and the navigation star needs to contain Complete position information and brightness information, and adjacent stars are regarded as binary stars, and cannot be used as navigation stars; the light from stars reaching the star sensor is considered as parallel light, which is diffused on the CCD image plane of the star sensor As a bright spot, the star pointed by the CCD optical axis is projected to the center of the image plane; the conversion formula of the coordinates of the navigation star in the inertial coordinate system to the coordinates in the star map image is as follows:

Among them, (N _x , N _y ) is the resolution of the CCD in the star sensor, (FOV _x , FOV _y ) is the size of the field of view of the CCD, (α _i , δ _i ) are the right ascension and declination of the observed star, respectively, (α, δ) is the direction of the optical axis of the CCD; the optical axis of the CCD always points to the position of the navigation star in the inertial coordinates.

As shown in Fig. 3, the observed star in the center of the field of view or close to the center of the field of view is selected as the main star S _s , according to the neighborhood size R of the main star, the observed star within the neighborhood is regarded as the neighboring star of the main star, The neighborhood is divided into n rings on average along the radial direction of the main star, and the neighboring stars in the neighborhood only belong to a certain ring. According to the position information of the main star and its neighbors on the star map image, count the The average plane distance between the neighboring star and the main star; the specific method is:

Assuming that n rings are marked as C0, C1, ..., Cn-1 from inside to outside, and the radius of the neighborhood of the main star is R, then the inner boundary of the i-th (i=0,...,n-1) ring and the outer boundary are expressed as i*R/n and (i+1)*R/n respectively; therefore, the coordinates of the neighboring star on the i-th ring should satisfy the following conditions:

i=0,...,n-1;

Among them, (x0, y0) and (x, y) are the coordinates of the center of mass of the main star and the neighboring star on the star map image respectively, and n is the number of rings in which the main star neighborhood is equally divided;

Assuming that the number of neighboring stars on each ring is represented as Ni (i=0,...,n-1), the average plane distance between the main star and the neighboring star on the i-th ring can be expressed as:

i=0,...n-1

Among them, (xij, yij) is the barycenter coordinates of the jth neighbor star on the i-th ring on the star map image, and Ni is the number of neighboring stars on the i-th ring.

As shown in Figure 4, different navigation stars may have the same code value, and some code values only correspond to a certain navigation star, that is, there is a one-to-one and one-to-many relationship between the navigation star and the code value; For this feature, it is proposed to determine the candidate matching results according to the code value of the observed star, and then use the average plane distance between the main star and the neighboring star to obtain the final identification result from the candidate matching results; in addition, due to the influence of noise, the same observed star The encoding value of will have certain fluctuations, so when identifying, only need to compare the encoding values in a certain range of variation to obtain candidate matching results without searching the entire navigation star feature library; thus, based on a small number of comparisons, The recognition result can be obtained, which speeds up the speed of star recognition.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. within range.

Claims (8)

1. it is a kind of based on integrated mode from primary recognition methodss, it is characterised in that

The contiguous range of primary is divided into into from inside to outside equidistant annulus, primary is put down with the average of adjacent star on each annulus Feature of the identity distance from composition primary under radial mode；The number of adjacent star, the coding obtained using code base on each annulus It is worth the feature under coding mode for primary；Feature of the combination primary under radial mode and coding mode constitutes primary in combination Characteristic vector under pattern；

Adjacent star on each annulus is apart from concrete grammar with the mean level of the sea of primary：

N annulus is labeled as successively from inside to outside C0, C1 ..., Cn-1, and the radius of neighbourhood of primary is R, then the i-th (i=0 ..., n- 1) inner boundary and external boundary of individual annulus is expressed as i*R/n and (i+1) * R/n, the seat of the adjacent star on i-th annulus Mark meets following condition：

$i\&times;R/n<\sqrt{{(x-x_0)}^2+{(y-y_0)}^2}\&le;(i+1)\&times;R/n,i=0,...,n-1;$

Wherein, (x₀, y₀) and (x, y) be respectively the center-of-mass coordinate of primary and adjacent star on star map image, n is put down for primary neighborhood The annulus number for dividing；

The number of adjacent star is expressed as Ni (i=0 ..., n-1) on each annulus, and the adjacent star on primary and i-th annulus is put down Plan range is expressed as：

$D_i=\frac{1}{N_i}\underset{j=1}{\overset{N_i}{\&Sigma;}}\sqrt{{(x_{ij}-x_0)}^2+{(y_{ij}-y_0)}^2},i=0,...n-1;$

Wherein, (x_ij, y_ij) it is the center-of-mass coordinate of j-th adjacent star on star map image on i-th annulus, Ni is on i-th annulus The number of adjacent star, the mean level of the sea distance on n annulus constitutes feature of the primary under radial mode, is expressed as：

D_vector={ D₀,D₁,…,D_n-1}；

The optical axis of CCD is pointed to one by one the nautical star in fundamental catalog, the characteristic vector corresponding to nautical star is generated, and is preserved For the form of data base, the feature database of nautical star is formed；

The hunting zone in nautical star feature database is reduced using the encoded radio in primary characteristic vector, by the characteristic vector of primary Matched with the characteristic vector in nautical star feature database, calculate feature in characteristic vector and the nautical star feature database of primary to The similarity of amount, so as to the result being identified.

2. as claimed in claim 1 based on integrated mode from primary recognition methodss, it is characterised in that obtaining primary in group Need before characteristic vector under syntype：

Calculate coordinate of the nautical star in star map image：Coordinate according to nautical star in inertial coodinate system, turns according to certain Rule is changed, coordinate of the nautical star in star map image is calculated；

Determine the star pattern of primary：The a certain observation star in visual field is taken as primary, according to the size of the radius of neighbourhood, primary is determined Adjacent star, the star pattern of primary is constituted by primary and adjacent star.

3. as claimed in claim 2 based on integrated mode from primary recognition methodss, it is characterised in that nautical star is sat in inertia The conversion formula of the coordinate in Coordinate Conversion to star map image in mark system is as follows：

$\begin{array}{c}{x}_r=\frac{N_x\&times;\cos \mathrm{\&delta;}\sin \left({\mathrm{\&alpha;}}_i-\mathrm{\&alpha;}\right)}{2\&times;\tan \left({\mathrm{FOV}}_x/2\right)\&times;\left({\mathrm{sin\&delta;}}_i\&times;\sin \mathrm{\&delta;}+{\mathrm{cos\&delta;}}_i\&times;\cos \mathrm{\&delta;}\&times;\cos \left({\mathrm{\&alpha;}}_i-\mathrm{\&alpha;}\right)\right)}\\ y_r=\frac{N_y\&times;\left({\mathrm{sin\&delta;}}_i\&times;\cos \mathrm{\&delta;}-{\mathrm{cos\&delta;}}_i\&times;\sin \mathrm{\&delta;}\&times;\cos \left({\mathrm{\&alpha;}}_i-\mathrm{\&alpha;}\right)\right)}{2\&times;\tan \left({\mathrm{FOV}}_y/2\right)\&times;\left({\mathrm{sin\&delta;}}_i\&times;\sin \mathrm{\&delta;}+{\mathrm{cos\&delta;}}_i\&times;\cos \mathrm{\&delta;}\&times;\cos \left({\mathrm{\&alpha;}}_i-\mathrm{\&alpha;}\right)\right)}\end{array};$

Wherein, (N_x,N_y) for the resolution of CCD in star sensor, (FOV_x,FOV_y) for CCD visual fields size, (α_i,δ_i) respectively To observe the right ascension declination of star, (α, δ) is the optical axis direction of CCD；The optical axis of CCD points to all the time nautical star in inertial coordinate Position, this nautical star projects to the center of star map image.

4. it is as claimed in claim 2 based on integrated mode from primary recognition methodss, it is characterised in that choose field of view center or Person near field of view center observation star as primary, the star pattern complete in the hope of obtaining primary；Size and master according to neighborhood The position of star, determines the positional information of the adjacent star of primary, and by the positional information of primary and adjacent star the star pattern of primary is constituted.

5. as claimed in claim 1 based on integrated mode from primary recognition methodss, it is characterised in that primary is in coding mode Under feature：The number of adjacent star on each annulus is counted, using default code base, is compiled according to certain coding rule Code, feature of the encoded radio for obtaining as primary in coding mode.

6. as claimed in claim 5 based on integrated mode from primary recognition methodss, it is characterised in that the acquisition side of encoded radio Method is：

The number of the adjacent star on i-th annulus is N_i(i=1 ..., n), then the corresponding encoded radio table under coding mode of primary It is shown as：

$V_s=\underset{i=0}{\overset{n-1}{\&Sigma;}}{N}_i{b}^{n-i-1};$

Wherein b is code base.

7. as claimed in claim 1 based on integrated mode from primary recognition methodss, it is characterised in that with reference to primary radially Feature under pattern and coding mode constitutes primary feature in the combined mode, primary characteristic vector table in the combined mode It is shown as：

Vector={ V_s,D_vector}；

In nautical star feature database, the record corresponding to each nautical star is expressed as：

Record={ id, Vector }={ id, V_s,D_vector}；

Wherein, id for nautical star label, V_sEncoded radio corresponding to nautical star, i.e. nautical star are as primary in coding mode Under feature, mean level of the sea distances of the D_vector by nautical star as the adjacent star on primary and n annulus in neighborhood constitute Feature of the primary under radial mode.

8. as claimed in claim 1 based on integrated mode from primary recognition methodss, it is characterised in that the process of primary identification It is expressed as：

Result=min { diff { Vector_s,Vector_c}},V_s∈Vector_s,V_c∈Vector_c,V_c∈[V_s-ε₁,V_s-ε₂]；

Wherein, V_sThe encoded radio in characteristic vector corresponding to nautical star s, V_cThe spy being characterized corresponding to the nautical star c in storehouse Levy the encoded radio in vector, ε₁And ε₂For encoded radio institute tolerance.