Infrared target type identification method and device based on emission position guided sampling matching

Abstract

The invention relates to the field of remote sensing image processing and machine vision application, provides an infrared target type identification method and device based on emission position guided sampling matching, and aims to solve the problem that the consumption of traditional global template matching operation resources is too large. According to the main scheme, the method comprises the following steps: pre-establishing a mapping relation from a transmitting position to a target possible type, estimating the transmitting position by combining target motion information and energy information in a prediction process, and then reducing the number of types needing to be identified according to the mapping relation, lowering a template to be matched, and improving the accuracy and speed of target type identification. The main technology comprises the following steps: establishing a mapping relation from a transmitting position to a target possible type; target motion information and energy information are combined, or multi-target collaborative information is combined to realize estimation of longitude and latitude of a transmitting position; and sampling a global type matching template by using the obtained longitude and latitude of the emission position and combining with the established mapping model to obtain a type vector, thereby realizing final infrared target type identification.

Description

Technical Field

[0001] The invention belongs to the field of remote sensing image processing and machine vision applications, and in particular relates to an infrared target type recognition method and device guided by emission position sampling matching. Background Art

[0002] Infrared target type recognition is the core of infrared search and tracking system. At present, type recognition is usually achieved by building a global type template library and matching one by one. However, due to the large number of target types in the global range, matching one by one will inevitably waste a lot of computing resources. Therefore, how to select some templates to be matched from many target types is the key. Each target must be emitted from a certain launch position located in a fixed area, so a mapping model can be established in advance according to the regional longitude and latitude range, the longitude and latitude of the launch position, and the target type. For the target to be predicted, the longitude and latitude coordinates of its launch point can be inferred based on the known information combined with the physical process, so as to determine the area and launch position of the launch point, and select the types that meet the requirements from the mapping model, and sort the types to be matched from near to far according to the distance between the launch point and the launch position. Therefore, the number of types that need to be identified can be reduced by establishing a mapping model and predicting the longitude and latitude of the launch point of the target to be identified. Summary of the invention

[0003] The purpose of the present invention is to guide the sampling matching library through the emission position, thereby solving the problem that a large amount of computing resources will be wasted when the existing method needs to build a global type template library and match it one by one to achieve type recognition. While ensuring the recognition accuracy, the speed of infrared target type recognition is improved.

[0004] The technical solution adopted by the present invention is as follows:

[0005] The present invention provides an infrared target type recognition method based on emission position guided sampling matching, comprising the following steps:

[0006] Step 1: Pre-establish a mapping model, pre-establish a mapping relationship between the launch position and the possible target type, specifically including real launch position-type list mapping, virtual launch position-type list mapping, regional geographic information-launch position list mapping, and finally establish regional geographic information-launch position list-type list mapping, obtain a mapping model, and proceed to step 2;

[0007] Step 2: Estimation of the launch position, which is achieved by combining the target motion information and energy information, or estimating the longitude and latitude of the launch position by using multi-target collaborative information to obtain the longitude and latitude of the launch position, and then proceed to step 3;

[0008] Step 3: Use the longitude and latitude of the launch position obtained in step 2 and the mapping model established in step 1 to sample the global type matching template and obtain the type vector to achieve the final infrared target type recognition.

[0009] In the above scheme, step 1 comprises the following steps:

[0010] Create a mapping between real launch location and type list:

[0011] Step 1.1: Establish the real launch position-type list mapping based on the real launch information:

[0012] f 1 :L 1 →M 1

[0013] Among them, f 1 Represents the set L 1 The elements in are mapped to the set M 1 Function of the elements in, (rx, ry)∈L 1 Represent the longitude and latitude of the actual launch location, M 1 A list collection of all types contained in the real launch position;

[0014] Create a virtual launch location-type list mapping:

[0015] Step 1.2: Combine historical target launch data to establish a virtual launch position-type list mapping, and calculate the launch time t of the i-th data of each type i :

[0016] t i = inf{t i |E i (t) = Fitting(T i , E i )<θ 1}

[0017] Among them, T i 、E i Respectively represent the time variation information and energy variation information of the i-th data, Fitting(T i , E i ) indicates that T i The horizontal axis E i Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t i According to T i and E i The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 moment;

[0018] Step 1.3: Calculate the longitude cx of the location where the i-th data of each type is transmitted i and latitude cy i :

[0019] xx i ={λ i (t i )|λ i (t) = Fitting(T i ,λ i )}

[0020]

[0021] Among them, λ i , Respectively represent the longitude change information and latitude change information of the i-th data;

[0022] Step 1.4: Calculate the outlier Z of each type of emission position by the following formula. If Z is less than the threshold θ 2 , go to step 1.5, if Z is greater than the threshold θ 2 Go to step 1.6;

[0023]

[0024] Among them, Z represents the type of emission position outliers, n represents the total number of data contained in the type, and The types respectively indicate the average longitude and latitude of the launch location containing all data. Indicates the calculation (cx i ,cy i )arrive The distance Represents all data points to The average distance of

[0025] Step 1.5: With the geometric center of all data as the center point, establish the first batch of virtual emission position-type list mappings:

[0026] f 2 :L 2 →M 2

[0027] Among them, f 2 Represents the set L 2 The elements in are mapped to the set M 2 The function of the elements in (vx G ,vy G )∈L 2 They represent the longitude and latitude of the virtual launch position with the geometric center of all data as the virtual launch position, M 2A collection of lists of all types included in the first batch of virtual launch positions;

[0028] Step 1.6: Clustering, obtaining the second batch of virtual emission position-type list mappings:

[0029] f 3 :L 3 →M 3

[0030] Among them, f 3 Represents the set L 3 The elements in are mapped to the set M 3 The function of the elements in (vx C ,vy C )∈L 3 They represent the longitude and latitude of the virtual launch position obtained by clustering, M 3 A list of all types included in the second batch of virtual launch positions;

[0031] Step 1.7: Gather the first batch of virtual launch position-type list mappings obtained in step 1.5 and the second batch of virtual launch position-type list mappings obtained in step 1.6 to establish virtual launch position-type list mappings:

[0032] f 4 :L 4 →M 4

[0033] Among them, f 4 Represents the set L 4 The elements in are mapped to the set M 4 Function of the elements in, (vx, vy)∈L 4 =L 2 ∪L 3 Respectively represent the longitude and latitude of the virtual launch position, M 4 =M 2 ∪M 3 A list of all types contained in the virtual launch position;

[0034] Create a regional geographic information-launch location list mapping:

[0035] Step 1.8: Combine the latitude and longitude of the real launch location, the latitude and longitude of the virtual launch location obtained in step 1.7, and the regional geographic information to establish a mapping between regional geographic information and the launch location list, and divide the regional territory into several rectangles so that the union of the rectangles can cover the regional territory and the total area is minimized:

[0036]

[0037] Among them, Area krepresents the latitude and longitude range covered by region k, m represents the number of rectangles divided into region k, R j Represents the latitude and longitude range covered by the jth rectangle, It means that m rectangular areas R j merged together to form a larger area;

[0038] Step 1.9: Calculate the minimum distance min between the longitude and latitude of the virtual launch position (vx, vy) and the longitude and latitude of all real launch positions in the region k to which it belongs d (vx,vy):

[0039]

[0040] Where (rx, ry)∈Area k They respectively indicate that region k contains the longitude and latitude of all real launch positions, and the region to which the real launch position belongs and the region to which the virtual launch position belongs are directly determined by the data;

[0041] Step 1.10: Combine all real launch positions and virtual launch positions in the region and add the minimum distance min obtained in step 1.9 d (vx, vy) and threshold θ 3 For comparison, if min d (vx,vy) is less than the threshold θ 3 , then the virtual launch position is considered to coincide with the real launch position, and the longitude and latitude of the virtual launch position are not retained; if min d (vx, vy) is greater than the threshold θ 3 , the virtual launch position is considered to be a new launch position different from the real launch position, and the longitude and latitude of the virtual launch position are retained. The formula is as follows:

[0042] L k =(L 1 ∈Area k )∪((vx,vy)∈L 4 ∈Area k and min d (vx,vy)>θ 3 )

[0043] Among them, (x k ,y k )∈L k represent the longitude and latitude of all transmitting locations contained in area k, L k Contains all real launch positions and virtual launch positions that meet the conditions in area k;

[0044] Step 1.11: Create a regional geographic information-launch location list mapping:

[0045] f 5 :A→L

[0046] Among them, f 5 represents a function that maps elements in set A to elements in set L. Represents all regional geographic information, represents the set of all launch locations, p is the total number of regions, (x, y)∈L represents the longitude and latitude of the launch location respectively;

[0047] Create a mapping between regional geographic information, launch location list, and type list:

[0048] Step 1.12: Combining the real launch location-type list mapping obtained in step 1.1, the virtual launch location-type list mapping obtained in step 1.7, and the regional geographic information-launch location list mapping obtained in step 1.11, a regional geographic information-launch location list-type list mapping can be finally established;

[0049] If in step 1.10, a virtual launch position coincides with a real launch position, then extract the types that are not in the real launch position from the target type list of the virtual launch position, and add these types to the real launch position-type list mapping established in step 1.1; combine the virtual launch position-type list mapping obtained in step 1.7 with the supplemented real launch position-type list mapping, correspond all types to the set L of all launch positions obtained in step 1.11, and establish a launch position-type list mapping:

[0050] f 6 :L→M

[0051] Among them, f 6 represents a function that maps elements in set L to elements in set M, M = M 1 ∪M 4 A collection of lists of all types;

[0052] Step 1.13: Combine the regional geographic information-transmission location list mapping obtained in step 1.11 with the transmission location-type list mapping obtained in step 1.12 to establish a regional geographic information-transmission location list-type list mapping:

[0053] f 7 :A→L→M

[0054] Among them, f 7 It is a composite mapping function from set A to set L, and then from set L to set M.

[0055] In the above scheme, step 2 comprises the following steps:

[0056] Step 2.1: Calculate the launch time t of target o o :

[0057] t o = inf{t o |E o (t) = Fitting(T o , E o )<θ 1} Among them, T o 、E o Respectively represent the time variation information and energy variation information of the target o, Fitting(T o , E o ) indicates that T o The horizontal axis E o Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t o According to T o and E o The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 moment;

[0058] Step 2.2: Calculate the longitude x of the target launch point o and latitude y o :

[0059] x o ={λ o (t o )|λ o (t) = Fitting(T o ,λ o )}

[0060] Among them, λ o , They respectively represent the longitude change information and latitude change information of the target o.

[0061] In the above scheme, step 3 comprises the following steps:

[0062] Step 3.1: Based on all the regional geographic information A obtained in step 1.11, obtain the longitude and latitude (x o ,y o )Area List A((x o ,y o )):

[0063]

[0064] Step 3.2: According to the regional geographic information-transmission location list mapping in the regional geographic information-transmission location list-type list mapping established in step 1.13, obtain (xo ,y o ) corresponds to the launch position list L((x o ,y o )):

[0065] L((x o ,y o ))=f 7 (A((x o ,y o )))→Lwhere (ox,oy)∈L((x o ,y o )) respectively represent (x o ,y o ) corresponds to the longitude and latitude of the transmitting location in the area to which it belongs;

[0066] Step 3.3: Calculate (x o ,y o ) and the corresponding launch position list L((x o ,y o )) and sort the launch positions from small to large distances to obtain a list of sorted launch positions L S ((x o ,y o )):

[0067] L S ((x o ,y o ))=Sort((kx,ky)|(kx,ky)∈L((x o ,y o )), d((x o ,y o ), (kx,ky)))

[0068] Among them, (sx,sy)∈L S ((x o ,y o )) respectively represent the L((x o ,y o )) After sorting, the longitude and latitude of the launch position;

[0069] Step 3.4: According to the sorted launch position list L S ((x o ,y o ), combined with the launch location list-type list mapping in the regional geographic information-launch location list-type list mapping established in step 1.13, we get (x o ,y o ) corresponds to the type vector M((x o ,y o )):

[0070] M((x o ,y o ))=f 7 (L S ((x o ,y o )))→M

[0071] M((x o ,y o )) contains (x o ,y o ) All types contained in all emission positions after sorting the area to which they belong, to achieve global type matching template sampling;

[0072] Step 3.5: Based on the type vector obtained in step 3.4, use the type matching algorithm from top to bottom to calculate the target o and the type vector M((x o ,y o )) and select the type Model(o) with the highest similarity as the type of target o to achieve infrared target type recognition:

[0073]

[0074] Among them, S(0,mdl) indicates that the type matching algorithm is used to calculate the target o and M((x o ,y o )) in type mdl.

[0075] The present invention also provides an infrared target type recognition device guided by emission position sampling matching, comprising the following steps:

[0076] Mapping model pre-establishment module: mapping model pre-establishment, mapping relationship between launch position and possible target type pre-establishment, specifically including real launch position-type list mapping, virtual launch position-type list mapping, regional geographic information-launch position list mapping, and finally establishing regional geographic information-launch position list-type list mapping to obtain a mapping model;

[0077] Transmitting position estimation module: Transmitting position estimation is realized by combining target motion information and energy information, or multi-target collaborative information to estimate the longitude and latitude of the transmitting position to obtain the longitude and latitude of the transmitting position;

[0078] Type recognition module: Utilize the longitude and latitude of the emission location and combine the established mapping model to sample the global type matching template to obtain the type vector and realize the final infrared target type recognition.

[0079] In the above device, the specific implementation of the mapping model pre-establishment module includes the following steps:

[0080] Create a mapping between real launch location and type list:

[0081] Step 1.1: Establish the real launch position-type list mapping based on the real launch information:

[0082] f 1 :L 1 →M 1

[0083] Among them, f 1 Represents the set L 1 The elements in are mapped to the set M 1 Function of the elements in, (rx, ry)∈L 1 Represent the longitude and latitude of the actual launch location, M 1 A list collection of all types contained in the real launch position;

[0084] Create a virtual launch location-type list mapping:

[0085] Step 1.2: Combine historical target launch data to establish a virtual launch position-type list mapping, and calculate the launch time t of the i-th data of each type i :

[0086] t i = inf{t i |E i (t) = Fitting(T i , E i )<θ 1}

[0087] Among them, T i 、E i Respectively represent the time variation information and energy variation information of the i-th data, Fitting(T i , E i ) indicates that T i The horizontal axis E i Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t i According to T i and E i The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 moment;

[0088] Step 1.3: Calculate the longitude cx of the location where the i-th data of each type is transmitted i and latitude cy i :

[0089] xx i ={λ i (t i )|λ i(t) = Fitting(T i ,λ i )}

[0090]

[0091] Among them, λ i , Respectively represent the longitude change information and latitude change information of the i-th data;

[0092] Step 1.4: Calculate the outlier Z of each type of emission position by the following formula. If Z is less than the threshold θ 2 , go to step 1.5, if Z is greater than the threshold θ 2 Go to step 1.6;

[0093]

[0094] Among them, Z represents the type of emission position outliers, n represents the total number of data contained in the type, and The types respectively indicate the average longitude and latitude of the launch location containing all data. Indicates the calculation (cx i ,cy i )arrive The distance Represents all data points to The average distance of

[0095] Step 1.5: With the geometric center of all data as the center point, establish the first batch of virtual emission position-type list mappings:

[0096] f 2 :L 2 →M 2

[0097] Among them, f 2 Represents the set L 2 The elements in are mapped to the set M 2 The function of the elements in (vx G ,vy G )∈L 2 They represent the longitude and latitude of the virtual launch position with the geometric center of all data as the virtual launch position, M 2 A collection of lists of all types included in the first batch of virtual launch positions;

[0098] Step 1.6: Clustering, obtaining the second batch of virtual emission position-type list mappings:

[0099] f 3 :L 3 →M3

[0100] Among them, f 3 Represents the set L 3 The elements in are mapped to the set M 3 The function of the elements in (vx C ,vy C )∈L 3 They represent the longitude and latitude of the virtual launch position obtained by clustering, M 3 A list of all types included in the second batch of virtual launch positions;

[0101] Step 1.7: Gather the first batch of virtual launch position-type list mappings obtained in step 1.5 and the second batch of virtual launch position-type list mappings obtained in step 1.6 to establish virtual launch position-type list mappings:

[0102] f 4 :L 4 →→→M 4

[0103] Among them, f 4 Represents the set L 4 The elements in are mapped to the set M 4 Function of the elements in, (vx, vy)∈L 4 =L 2 ∪L 3 Respectively represent the longitude and latitude of the virtual launch position, M 4 =M 2 ∪M 3 A list of all types contained in the virtual launch position;

[0104] Create a regional geographic information-launch location list mapping:

[0105] Step 1.8: Combine the latitude and longitude of the real launch location, the latitude and longitude of the virtual launch location obtained in step 1.7, and the regional geographic information to establish a mapping between regional geographic information and the launch location list, and divide the regional territory into several rectangles so that the union of the rectangles can cover the regional territory and the total area is minimized:

[0106]

[0107] Among them, Area k represents the latitude and longitude range covered by region k, m represents the number of rectangles divided into region k, R j Represents the latitude and longitude range covered by the jth rectangle, It means that m rectangular areas R j merged together to form a larger area;

[0108] Step 1.9: Calculate the minimum distance min between the longitude and latitude of the virtual launch position (vx, vy) and the longitude and latitude of all real launch positions in the region k to which it belongs d (vx,vy):

[0109]

[0110] Among them, (rx,ry)∈Area k They respectively indicate that region k contains the longitude and latitude of all real launch positions, and the region to which the real launch position belongs and the region to which the virtual launch position belongs are directly determined by the data;

[0111] Step 1.10: Combine all real launch positions and virtual launch positions in the region and add the minimum distance min obtained in step 1.9 d (vx,vy) and threshold θ 3 For comparison, if min d (vx, vy) is less than the threshold θ 3 , then the virtual launch position is considered to coincide with the real launch position, and the longitude and latitude of the virtual launch position are not retained; if min d (vx, vy) is greater than the threshold θ 3 , the virtual launch position is considered to be a new launch position different from the real launch position, and the longitude and latitude of the virtual launch position are retained. The formula is as follows:

[0112] L k =(L 1 ∈Area k )∪((vx,vy)∈L 4 ∈Area k and min d (vx,vy)>θ 3 )

[0113] Among them, (x k ,y k )∈L k represent the longitude and latitude of all transmitting locations contained in area k, L k Contains all real launch positions and virtual launch positions that meet the conditions in area k;

[0114] Step 1.11: Create a regional geographic information-launch location list mapping:

[0115] f 5 :A→L

[0116] Among them, f 5 represents a function that maps elements in set A to elements in set L. Represents all regional geographic information, represents the set of all launch locations, p is the total number of regions, (x, y)∈L represents the longitude and latitude of the launch location respectively;

[0117] Create a mapping between regional geographic information, launch location list, and type list:

[0118] Step 1.12: Combining the real launch location-type list mapping obtained in step 1.1, the virtual launch location-type list mapping obtained in step 1.7, and the regional geographic information-launch location list mapping obtained in step 1.11, a regional geographic information-launch location list-type list mapping can be finally established;

[0119] If in step 1.10, a virtual launch position coincides with a real launch position, then extract the types that are not in the real launch position from the target type list of the virtual launch position, and add these types to the real launch position-type list mapping established in step 1.1; combine the virtual launch position-type list mapping obtained in step 1.7 with the supplemented real launch position-type list mapping, correspond all types to the set L of all launch positions obtained in step 1.11, and establish a launch position-type list mapping:

[0120] f 6 :L→M

[0121] Among them, f 6 represents a function that maps elements in set L to elements in set M, M = M 1 ∪M 4 A collection of lists of all types;

[0122] Step 1.13: Combine the regional geographic information-transmission location list mapping obtained in step 1.11 with the transmission location-type list mapping obtained in step 1.12 to establish a regional geographic information-transmission location list-type list mapping:

[0123] f 7 :A→L→M

[0124] Among them, f 7 It is a composite mapping function from set A to set L, and then from set L to set M.

[0125] In the above device, the implementation of the transmission position estimation module includes the following steps:

[0126] Step 2.1: Calculate the launch time t of target o o :

[0127] t o = inf{t o |E o (t) = Fitting(T o , Eo )<θ 1} Among them, T o 、E o Respectively represent the time variation information and energy variation information of the target o, Fitting(T o , E o ) indicates that T o The horizontal axis E o Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t o According to T o and E o The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 moment;

[0128] Step 2.2: Calculate the longitude x of the target launch point o and latitude y o :

[0129] x o ={λ o (t o )|λ o (t) = Fitting(T o ,λ o ))

[0130] Among them, λ o , They respectively represent the longitude change information and latitude change information of the target o.

[0131] In the above device, the implementation of the type identification module includes the following steps:

[0132] Step 3.1: Based on all the regional geographic information A obtained in step 1.11, obtain the longitude and latitude (x o ,y o )Area List A((x o ,y o )):

[0133]

[0134] Step 3.2: According to the regional geographic information-transmission location list mapping in the regional geographic information-transmission location list-type list mapping established in step 1.13, obtain (x o ,y o ) corresponds to the launch position list L((x o ,y o )):

[0135] L((x o ,y o))=f 7 (A((x o ,y o )))→Lwhere (ox,oy)∈L((x o ,y o )) respectively represent (x o ,y o ) corresponds to the longitude and latitude of the transmitting location in the area to which it belongs;

[0136] Step 3.3: Calculate (x o ,y o ) and the corresponding launch position list L((x o ,y o )) and sort the launch positions from small to large distances to obtain a list of sorted launch positions L S ((x o ,y o )):

[0137] L S ((x o ,y o ))=Sort(((kx,ky)|(kx,ky)∈L((x o ,y o )), d((x o ,y o ), (kx,ky)))

[0138] Among them, (sx,sy)∈L S ((x o ,y o )) respectively represent the L((x o ,y o )) After sorting, the longitude and latitude of the launch position;

[0139] Step 3.4: According to the sorted launch position list L S ((x o ,y o ), combined with the launch location list-type list mapping in the regional geographic information-launch location list-type list mapping established in step 1.13, we get (x o ,y o ) corresponds to the type vector M((x o ,y o )):

[0140] M((x o ,y o ))=f 7 (L S ((x o ,y o )))→M

[0141] M((x o ,y o )) contains (x o ,y o ) All types contained in all emission positions after sorting the area to which they belong, to achieve global type matching template sampling;

[0142] Step 3.5: Based on the type vector obtained in step 3.4, use the type matching algorithm from top to bottom to calculate the target o and the type vector M((x o ,y o )) and select the type Model(o) with the highest similarity as the type of target o to achieve infrared target type recognition:

[0143]

[0144] Among them, S(o,mdl) represents the type matching algorithm used to calculate the target o and M((x o ,y o )) in type mdl.

[0145] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0146] 1. The core function of the present invention is to sample the type matching library, which greatly improves the recognition speed while ensuring a high target recognition rate.

[0147] 2. The emission position guided sampling matching library method proposed in the present invention has a wide range of applications and can be widely embedded in various infrared aerial target type recognition tasks as a pre-processing for recognition.

[0148] 3. The mapping model establishment method and the emission point estimation strategy are designed comprehensively and thoughtfully, covering a variety of special cases, giving it strong adaptability when facing various complex scenarios.

[0149] 4. The mapping model establishment method fully considers the missing of real information and historical data, efficiently integrates data, and constructs a complete mapping relationship.

[0150] 5. The launch point estimation strategy addresses the problems of difficult detection and incomplete data in the early stages of target launch. It uses existing information to accurately estimate the longitude and latitude of the target launch point, laying the foundation for accurate sampling of the subsequent type matching library. BRIEF DESCRIPTION OF THE DRAWINGS

[0151] Figure 1 It is the overall flow chart of the present invention;

[0152] Figure 2 It is a schematic diagram for identifying the present invention. DETAILED DESCRIPTION

[0153] The present invention is further described in detail below in conjunction with test examples and specific implementation methods. However, this should not be understood as the scope of the above subject matter of the present invention being limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

[0154] The present invention provides an infrared target type recognition method and device guided by emission position sampling matching. The technical problem to be solved is how to sample some templates to be matched from a large number of target types, thereby achieving a high target recognition rate and high speed infrared target type recognition method and device guided by emission position sampling matching library. The entire algorithm design structure framework is as follows Figure 1 As shown, the steps include:

[0155] Create a real launch location-type list mapping.

[0156] Step 1.1: Establish the real launch position-type list mapping based on the real launch information:

[0157] f 1 :L 1 →M 1

[0158] Where (rx, ry)∈L 1 Represent the longitude and latitude of the actual launch location, M 1 A collection of lists of all types contained in the actual launch position.

[0159] Create a virtual launch location-type list mapping.

[0160] Step 1.2: Combined with historical target launch data, a virtual launch position-type list mapping can be established. Calculate the launch time t of the i-th data of each type i :

[0161] t i = inf{t i |E i (t) = Fitting(T i , E i )<θ 1}

[0162] Among them, T i 、E i Respectively represent the time variation information and energy variation information of the i-th data, Fitting(T i , E i ) indicates that T i The horizontal axis E i Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t iAccording to T i and E i The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 In this example, a quadratic polynomial fit is used, θ 1 =1000;

[0163] Step 1.3: Calculate the longitude cx of the location where the i-th data of each type is transmitted i and latitude cy i :

[0164] xx i ={λ i (t i )|λ i (t) = Fitting(T i ,λ i )}

[0165]

[0166] Among them, λ i , Respectively represent the longitude change information and latitude change information of the i-th data;

[0167] Step 1.4: Calculate the outlier Z of each type of emission position by the following formula. If Z is less than the threshold θ 2 , go to step 1.5, if Z is greater than the threshold θ 2 Proceed to step 1.6.

[0168]

[0169] Among them, Z represents the type of emission position outliers, n represents the total number of data contained in the type, and The types respectively indicate the average longitude and latitude of the launch location containing all data. Indicates the calculation (cx i ,cy i )arrive The distance Represents all data points to In this example, the Haversine formula is used to calculate the distance between two points on the earth's surface, θ 2 =0.5;

[0170] Step 1.5: With the geometric center of all data as the center point, establish the first batch of virtual emission position-type list mappings:

[0171] f 2 :L 2 →M2

[0172] Among them, (vx G ,vy G )∈L 2 They represent the longitude and latitude of the virtual launch position with the geometric center of all data as the virtual launch position, M 2 A collection of lists of all types included in the first batch of virtual launch positions;

[0173] Step 1.6: Clustering, obtaining the second batch of virtual emission position-type list mappings:

[0174] f 3 :L 3 →M 3

[0175] Among them, (vx C ,vy C )∈L 3 They represent the longitude and latitude of the virtual launch position obtained by clustering, M 3 is the set of all types of lists contained in the second batch of virtual launch positions. In this example, DBSCAN clustering is used;

[0176] Step 1.7: Gather the first batch of virtual launch position-type list mappings obtained in step 1.5 and the second batch of virtual launch position-type list mappings obtained in step 1.6 to establish virtual launch position-type list mappings:

[0177] f 4 :L 4 →M 4

[0178] Where (vx,vy)∈L 4 =L 2 ∪L 3 Respectively represent the longitude and latitude of the virtual launch position, M 4 =M 2 ∪M 3 A collection of lists of all types contained in the virtual emission position.

[0179] Establish regional geographic information - launch location list mapping.

[0180] Step 1.8: Combine the latitude and longitude of the real launch location, the latitude and longitude of the virtual launch location obtained in step 1.7, and the regional geographic information to establish a mapping between regional geographic information and the launch location list. Divide the regional territory into several rectangles so that the union of the rectangles can cover the regional territory and the total area is minimal:

[0181]

[0182] Among them, Areak represents the latitude and longitude range covered by region k, m represents the number of rectangles divided into region k, R j Indicates the latitude and longitude range covered by the jth rectangle;

[0183] Step 1.9: Calculate the minimum distance min between the longitude and latitude of the virtual launch position (vx, vy) and the longitude and latitude of all real launch positions in the region k to which it belongs d (vx, vy):

[0184]

[0185] Among them, (rx,ry)∈Area k They respectively represent that region k contains the longitude and latitude of all real launch positions. The region to which the real launch position belongs and the region to which the virtual launch position belongs can be directly determined by the data. In this example, the Haversine formula is used to calculate the distance between two points on the earth's surface;

[0186] Step 1.10: Combine all the real launch positions and virtual launch positions in the region by the following formula. d (vx,vy) and threshold θ 3 For comparison. d (vx, vy) is less than the threshold θ 3 , then the virtual launch position is considered to coincide with the real launch position, and the longitude and latitude of the virtual launch position are not retained; if min d (vx, vy) is greater than the threshold θ 3 , the virtual launch position is considered to be a new launch position different from the real launch position, and the longitude and latitude of the virtual launch position are retained.

[0187] L k =(L 1 ∈Area k )∪((vx,vy)∈L 4 ∈Area k and min d (vx,vy)>θ 3 )

[0188] Among them, (x k ,y k )∈L k Respectively represent the longitude and latitude of all launch locations contained in area k. In this example, θ 3 =100;

[0189] Step 1.11: Create a regional geographic information-launch location list mapping:

[0190] f 5 :A-→L

[0191] in, Represents all regional geographic information, represents the set of all launch locations, p is the total number of regions, and (x, y)∈L represents the longitude and latitude of the launch location respectively.

[0192] Establish regional geographic information-transmission location list-type list mapping.

[0193] Step 1.12: Combine the real launch position-type list mapping obtained in step 1.1, the virtual launch position-type list mapping obtained in step 1.7, and the regional geographic information-launch position list mapping obtained in step 1.11 to finally establish the regional geographic information-launch position list-type list mapping. If there is a virtual launch position that overlaps with the real launch position in step 1.10, extract other types contained in the virtual launch position that are different from the types contained in the overlapping real launch position, and supplement the real launch position-type list mapping established in step 1.1. Combine the supplemented real launch position-type list mapping with the virtual launch position-type list mapping obtained in step 1.7, correspond all types to the set L of all launch positions obtained in step 1.11, and establish the launch position-type list mapping:

[0194] f 6 :L→M

[0195] Where M = M 1 ∪M 4 A collection of lists of all types;

[0196] Step 1.13: Combine the regional geographic information-transmission location list mapping obtained in step 1.11 with the transmission location-type list mapping obtained in step 1.12 to establish a regional geographic information-transmission location list-type list mapping:

[0197] f 7 :A→L→M

[0198] Step 2.1: Calculate the launch time t of target o o :

[0199] t o = inf{t o |E o (t) = Fitting(T o , E o )<θ 1}

[0200] Among them, T o 、E o Respectively represent the time variation information and energy variation information of the target o, Fitting(T o, E o ) indicates that T o The horizontal axis E o Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t o According to T o and E o The fitting relationship predicts the time forward until the energy is less than the threshold θ 1 In this example, a quadratic polynomial fit is used, θ 1 =1000;

[0201] Step 2.2: Calculate the longitude x of the target launch point o and latitude y o :

[0202] x o ={λ o (t o )|λ o (t) = Fitting(T o ,λ o )}

[0203]

[0204] Among them, λ o , They respectively represent the longitude change information and latitude change information of the target o.

[0205] Step 3.1: Based on all the regional geographic information A obtained in step 1.11, obtain the longitude and latitude (x o ,y o )Area List A((x o ,y o )):

[0206]

[0207] Because the longitude and latitude range of the region is divided into blocks, there may be overlaps between regions, resulting in more than one region for the target launch point to belong to. Therefore, a list is used to store the regions to which the longitude and latitude of the launch point belong.

[0208] Step 3.2: According to the regional geographic information-transmission location list mapping in the regional geographic information-transmission location list-type list mapping established in step 1.13, obtain (x o ,y o ) corresponds to the launch position list L((x o ,y o )):

[0209] L((x o ,y o))=f 7 (A((x o ,y o )))→L

[0210] Among them, (ox,oy)∈L((x o ,y o )) respectively represent (x o ,y o ) corresponds to the longitude and latitude of the transmitting location in the area to which it belongs;

[0211] Step 3.3: Calculate (x o ,y o ) and the corresponding launch position list L((x o ,y o )) and sort the launch positions from small to large distances to obtain a list of sorted launch positions L S ((x o ,y o )):

[0212] L S ((x o ,y o ))=Sort({(kx,ky)|(kx,ky)∈L((x o ,y o ))},d((x o ,y o ), (kx,ky)))

[0213] Among them, (sx,sy)∈L S ((x o ,y o )) respectively represent the L((x o ,y o )) After sorting, the longitude and latitude of the transmitted position. In this example, the Haversine formula is used to calculate the distance between two points on the earth's surface;

[0214] Step 3.4: According to the sorted launch position list L S ((x o ,y o ), combined with the launch location-type list mapping in the regional geographic information-launch location list-type list mapping established in step 1.13, we get (x o ,y o ) corresponds to the type vector M((x o ,y o )):

[0215] M((x o ,y o ))=f 7(L S ((x o ,y o )))→M

[0216] M((x o ,y o )) contains (x o ,y o ) All types contained in all emission positions after sorting the area to which they belong, to achieve global type matching template sampling;

[0217] Step 3.5: Based on the type vector obtained in step 3.4, use the type matching algorithm from top to bottom to calculate the target o and the type vector M((x o ,y o )) and select the type Model(o) with the highest similarity as the type of target o to achieve infrared target type recognition:

[0218]

[0219] Among them, S(o,mdl) represents the type matching algorithm used to calculate the target o and M((x o ,y o )) in the type mdl. In this example, the type matching uses the dynamic time warping algorithm.

[0220] In summary, the present invention has the following characteristics:

[0221] 1. By establishing a mapping relationship between the launch position and the possible target type, and combining the target motion information and energy information to estimate the launch position, the problem of too many target types in the entire domain and the waste of computing resources for one-by-one matching is solved. This method significantly reduces the complexity of the template to be matched by reducing the number of types that need to be identified, thereby improving the accuracy and speed of target type identification.

[0222] 2. By constructing a mapping of real launch location-type list and a mapping of virtual launch location-type list, and combining regional geographic information, the problem of missing historical data or incomplete data at the initial stage of target launch is solved. This method integrates real data and historical data to build a complete mapping relationship, ensuring that target types can still be efficiently identified in complex scenarios.

[0223] 3. Through clustering and geometric center calculation, a virtual launch position-type list mapping is established to solve the problem of uneven distribution of target launch positions or many outliers. This method optimizes the distribution of virtual launch positions through clustering and geometric center calculation, ensures the robustness and adaptability of the mapping model, and further improves the accuracy of target type recognition.

[0224] 4. The problem of unclear area to which the target emission point belongs is solved by combining regional geographic information-transmission location list mapping and type list mapping. This method divides the area into several rectangles and combines the relationship between the emission location and the area to accurately determine the area to which the target emission point belongs, thereby achieving accurate sampling of the global type matching template.

[0225] 5. The complex similarity calculation problem in the target type recognition process is solved by combining the sorted emission position list with the type matching algorithm such as the dynamic time warping algorithm. This method sorts the emission positions by distance and calculates the similarity in sequence, ensuring that the recognition accuracy is guaranteed while greatly improving the recognition speed. It is suitable for various infrared aerial target type recognition tasks.

Claims

1. A method for infrared target type recognition based on emission position guided sampling matching, characterized in that: The steps include: Step 1: Pre-establish a mapping model, pre-establish a mapping relationship between the launch position and the possible target type, specifically including real launch position-type list mapping, virtual launch position-type list mapping, regional geographic information-launch position list mapping, and finally establish regional geographic information-launch position list-type list mapping, obtain a mapping model, and proceed to step 2; Step 2: Estimation of the launch position, which is achieved by combining the target motion information and energy information, or estimating the longitude and latitude of the launch position by using multi-target collaborative information to obtain the longitude and latitude of the launch position, and then proceed to step 3; Step 3: Use the longitude and latitude of the launch position obtained in step 2 and the mapping model established in step 1 to sample the global type matching template and obtain the type vector to achieve the final infrared target type recognition.

2. The infrared target type recognition method based on emission position guided sampling matching according to claim 1 is characterized in that: The step 1 comprises the following steps: Create a mapping between real launch location and type list: Step 1.1: Establish the real launch position-type list mapping based on the real launch information: f1: L1→M1 Wherein, f1 represents a function that maps elements in set L1 to elements in set M1, (rx, ry)∈L1 represents the longitude and latitude of the actual launch location, and M1 is a set of all type lists contained in the actual launch location; Create a virtual launch location-type list mapping: Step 1.2: Combine historical target launch data to establish a virtual launch position-type list mapping, and calculate the launch time t of the i-th data of each type i : t i =inf{t i |E i (t)=Fitting(T i ,E i )<θ1} Among them, T i 、E i Respectively represent the time variation information and energy variation information of the i-th data, Fitting(T i , E i ) indicates that T i The horizontal axis E i Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t i According to T i and E i The fitting relationship predicts the time forward until the energy is less than the threshold θ1; Step 1.3: Calculate the longitude cx of the location where the i-th data of each type is transmitted i and latitude cy i : cx i ={λ i (t i )|λ i (t)=Fitting(T i ,λ i )} Among them, λ i , Respectively represent the longitude change information and latitude change information of the i-th data; Step 1.4: Calculate the outlier Z of each type of emission position by the following formula. If Z is less than the threshold θ2, proceed to step 1.

5. If Z is greater than the threshold θ2, proceed to step 1.

6. Among them, Z represents the type of emission position outliers, n represents the total number of data contained in the type, and The types respectively indicate the average longitude and latitude of the launch location containing all data. Indicates the calculation (cx i ,cy i )arrive The distance Represents all data points to The average distance of Step 1.5: With the geometric center of all data as the center point, establish the first batch of virtual emission position-type list mappings: f2: L2→M2 Where f2 represents a function that maps elements in set L2 to elements in set M2, (vx G ,vy G )∈L2 respectively represent the longitude and latitude of the virtual launch position with the geometric center of all data as the virtual launch position, and M2 is the set of all type lists contained in the first batch of virtual launch positions; Step 1.6: Clustering, obtaining the second batch of virtual emission position-type list mappings: f3: L3 → M3 Where f3 represents a function that maps elements in set L3 to elements in set M3, (vx C vy C )∈L3 represent the longitude and latitude of the virtual launch position obtained by clustering, M3 is the set of all type lists contained in the second batch of virtual launch positions; Step 1.7: Gather the first batch of virtual launch position-type list mappings obtained in step 1.5 and the second batch of virtual launch position-type list mappings obtained in step 1.6 to establish virtual launch position-type list mappings: f4: L4 → M4 Wherein, f4 represents a function that maps elements in set L4 to elements in set M4, (vx, vy)∈L4=L2UL3 represent the longitude and latitude of the virtual launch position respectively, and M4=M2UM3 is a set of all type lists contained in the virtual launch position; Create a regional geographic information-launch location list mapping: Step 1.8: Combine the latitude and longitude of the real launch position, the latitude and longitude of the virtual launch position obtained in step 1.7, and the regional geographic information to establish a mapping between regional geographic information and the launch position list, and divide the regional territory into several rectangles so that the union of the rectangles can cover the regional territory and the total area is minimized: Among them, Area k represents the latitude and longitude range covered by region k, m represents the number of rectangles divided into region k, R j Represents the latitude and longitude range covered by the jth rectangle, It means that m rectangular areas R j merged together to form a larger area; Step 1.9: Calculate the minimum distance min between the virtual launch location longitude and latitude (vx, vy) and the longitude and latitude of all real launch locations in the region k to which it belongs d (vx, vy): Where (rx, ry)∈Area k They respectively indicate that region k contains the longitude and latitude of all real launch positions, and the region to which the real launch position belongs and the region to which the virtual launch position belongs are directly determined by the data; Step 1.10: Combine all real launch positions and virtual launch positions in the region and add the minimum distance min obtained in step 1.9 d (vx,vy) is compared with the threshold θ3. If min d (vx, vy) is less than the threshold θ3, then the virtual launch position is considered to coincide with the real launch position, and the longitude and latitude of the virtual launch position are not retained; if min d If (vx, vy) is greater than the threshold θ3, the virtual launch position is considered to be a new launch position different from the real launch position, and the longitude and latitude of the virtual launch position are retained. The formula is as follows: L k =(L1∈Area k )∪((vx,vy)∈L4∈Area k and min d (vx,vy)>θ3) Among them, (x k ,y k )∈L k represent the longitude and latitude of all transmitting locations contained in area k, L k Contains all real launch positions and virtual launch positions that meet the conditions in area k; Step 1.11: Create a regional geographic information-launch location list mapping: f5: A→L Among them, f5 represents the function that maps the elements in set A to the elements in set L. Represents all regional geographic information, represents the set of all launch locations, p is the total number of regions, (x, y)∈L represents the longitude and latitude of the launch location respectively; Create a mapping between regional geographic information, launch location list, and type list: Step 1.12: Combining the real launch location-type list mapping obtained in step 1.1, the virtual launch location-type list mapping obtained in step 1.7, and the regional geographic information-launch location list mapping obtained in step 1.11, a regional geographic information-launch location list-type list mapping can be finally established; If in step 1.10, a virtual launch position coincides with a real launch position, then extract the types that are not in the real launch position from the target type list of the virtual launch position, and add these types to the real launch position-type list mapping established in step 1.1; combine the virtual launch position-type list mapping obtained in step 1.7 with the supplemented real launch position-type list mapping, correspond all types to the set L of all launch positions obtained in step 1.11, and establish a launch position-type list mapping: f6: L→M Wherein, f6 represents a function that maps elements in set L to elements in set M, and M=M1UM4 is a set of lists of all types; Step 1.13: Combine the regional geographic information-transmission location list mapping obtained in step 1.11 with the transmission location-type list mapping obtained in step 1.12 to establish a regional geographic information-transmission location list-type list mapping: f7: A→L→M Among them, f7 is a composite mapping function from set A to set L, and then from set L to set M.

3. The infrared target type recognition method based on emission position guided sampling matching according to claim 2 is characterized in that: The step 2 comprises the following steps: Step 2.1: Calculate the launch time t of target o o : t o = inf{t o | E o (t) = Fitting(T o , E o ) < θ1}, where, T o 、E o Respectively represent the time variation information and energy variation information of the target o, Fitting(T o , E o ) indicates that T o The horizontal axis E o Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t o According to T o and E o The fitting relationship predicts the time forward until the energy is less than the threshold θ1; Step 2.2: Calculate the longitude x of the target launch point o and latitude y o : x o ={λ o (t o )|λ o (t)=Fitting(T o ,λ o )} Among them, λ o , They respectively represent the longitude change information and latitude change information of the target o.

4. The infrared target type recognition method based on emission position guided sampling matching according to claim 3 is characterized in that: The step 3 comprises the following steps: Step 3.1: Based on all the regional geographic information A obtained in step 1.11, obtain the longitude and latitude (x o ,y o )Area List A((x o ,y o )): Step 3.2: According to the regional geographic information-transmission location list mapping in the regional geographic information-transmission location list-type list mapping established in step 1.13, obtain (x o ,y o ) corresponds to the launch position list L((x o ,y o )): L((x o ,y o ))=f7(A((x o ,y o )))→Lwhere (ox,oy)∈L((x o ,y o )) respectively represent (x o ,y o ) corresponds to the longitude and latitude of the transmitting location in the area to which it belongs; Step 3.3: Calculate (x o ,y o ) and the corresponding launch position list L((x o ,y o )) and sort the launch positions from small to large distances to obtain a list of sorted launch positions L S ((x o ,y o )): L S ((x o ,y o ))=Sort((kx,ky)|(kx,ky)∈L((x o ,y o )),d((x o ,y o ),(kx,ky))) Among them, (sx,sy)∈L S ((x o ,y o )) respectively represent the L((x o ,y o )) After sorting, the longitude and latitude of the emitted location are: Step 3.4: According to the sorted launch position list L S ((x o ,y o ), combined with the launch location list-type list mapping in the regional geographic information-launch location list-type list mapping established in step 1.13, we get (x o ,y o ) corresponds to the type vector M((x o ,y o )): M((x o ,and o ))=f7(L S ((x o ,and o )))→M M((x o ,y o )) contains (x o ,y o ) After sorting the area to which it belongs, all types contained in all emission positions are obtained to achieve global type matching template sampling; Step 3.5: Based on the type vector obtained in step 3.4, use the type matching algorithm from top to bottom to calculate the target o and the type vector M((x o ,y o )) and select the type Model(o) with the highest similarity as the type of target o to achieve infrared target type recognition: Among them, S(o,mdl) represents the type matching algorithm used to calculate the target o and M((x o ,y o )) in type mdl.

5. An infrared target type recognition device guided by emission position sampling matching, characterized in that: The steps include: Mapping model pre-establishment module: mapping model pre-establishment, mapping relationship between launch position and possible target type pre-establishment, specifically including real launch position-type list mapping, virtual launch position-type list mapping, regional geographic information-launch position list mapping, and finally establishing regional geographic information-launch position list-type list mapping to obtain a mapping model; Transmitting position estimation module: Transmitting position estimation is realized by combining target motion information and energy information, or multi-target collaborative information to estimate the longitude and latitude of the transmitting position to obtain the longitude and latitude of the transmitting position; Type recognition module: Utilize the longitude and latitude of the emission location and combine the established mapping model to sample the global type matching template to obtain the type vector and realize the final infrared target type recognition.

6. The infrared target type recognition device guided by emission position sampling matching according to claim 5, characterized in that: The specific implementation of the mapping model pre-establishment module includes the following steps: Create a mapping between real launch location and type list: Step 1.1: Establish the real launch position-type list mapping based on the real launch information: f1: L1→M1 Wherein, f1 represents a function that maps elements in set L1 to elements in set M1, (rx, ry)∈L1 represents the longitude and latitude of the actual launch location, and M1 is a set of all type lists contained in the actual launch location; Create a virtual launch location-type list mapping: Step 1.2: Combine historical target launch data to establish a virtual launch position-type list mapping, and calculate the launch time t of the i-th data of each type i : t i =inf{t i |E i (t)=Fitting(T i ,E i )<θ1} Among them, T i 、E i Respectively represent the time variation information and energy variation information of the i-th data, Fitting(T i , E i ) indicates that T i The horizontal axis E i Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t i According to T i and E i The fitting relationship predicts the time forward until the energy is less than the threshold θ1; Step 1.3: Calculate the longitude cx of the location where the i-th data of each type is transmitted i and latitude cy i : cx i ={λ i (t i )|λ i (t)=Fitting(T i ,λ i )} Among them, λ i , Respectively represent the longitude change information and latitude change information of the i-th data; Step 1.4: Calculate the outlier Z of each type of emission position by the following formula. If Z is less than the threshold θ2, proceed to step 1.

5. If Z is greater than the threshold θ2, proceed to step 1.

6. Among them, Z represents the type of emission position outliers, n represents the total number of data contained in the type, and The types respectively indicate the average longitude and latitude of the launch location containing all data. Indicates the calculation (cx i ,cy i )arrive The distance Represents all data points to The average distance of Step 1.5: With the geometric center of all data as the center point, establish the first batch of virtual emission position-type list mappings: f2: L2→M2 Where f2 represents a function that maps elements in set L2 to elements in set M2, (vx G ,vy G )∈L2 respectively represent the longitude and latitude of the virtual launch position with the geometric center of all data as the virtual launch position, and M2 is the set of all type lists contained in the first batch of virtual launch positions; Step 1.6: Clustering, obtaining the second batch of virtual emission position-type list mappings: f3: L3 → M3 Where f3 represents a function that maps elements in set L3 to elements in set M3, (vx C ,vy C )∈L3 represent the longitude and latitude of the virtual launch position obtained by clustering, M3 is the set of all type lists contained in the second batch of virtual launch positions; Step 1.7: Gather the first batch of virtual launch position v type list mappings obtained in step 1.5 and the second batch of virtual launch position-type list mappings obtained in step 1.6 to establish a virtual launch position-type list mapping: f4: L4 → M4 Wherein, f4 represents a function that maps elements in set L4 to elements in set M4, (vx, vy)∈L4=L2UL3 represent the longitude and latitude of the virtual launch position respectively, and M4=M2UM3 is a set of all type lists contained in the virtual launch position; Create a regional geographic information-launch location list mapping: Step 1.8: Combine the latitude and longitude of the real launch position, the latitude and longitude of the virtual launch position obtained in step 1.7, and the regional geographic information to establish a mapping between regional geographic information and the launch position list, and divide the regional territory into several rectangles so that the union of the rectangles can cover the regional territory and the total area is minimized: Among them, Area k represents the latitude and longitude range covered by region k, m represents the number of rectangles divided into region k, R j Represents the latitude and longitude range covered by the jth rectangle, It means that m rectangular areas R j merged together to form a larger area; Step 1.9: Calculate the minimum distance min between the virtual launch location longitude and latitude (vx, vy) and the longitude and latitude of all real launch locations in the region k to which it belongs d (vx,vy): Where (rx, ry)∈Area k They respectively indicate that region k contains the longitude and latitude of all real launch positions, and the region to which the real launch position belongs and the region to which the virtual launch position belongs are directly determined by the data; Step 1.10: Combine all real launch positions and virtual launch positions in the region and add the minimum distance min obtained in step 1.9 d (vx,vy) is compared with the threshold θ3. If min d (vx,vy) is less than the threshold θ3, then the virtual launch position is considered to coincide with the real launch position, and the longitude and latitude of the virtual launch position are not retained; if min d If (vx, vy) is greater than the threshold θ3, the virtual launch position is considered to be a new launch position different from the real launch position, and the longitude and latitude of the virtual launch position are retained. The formula is as follows: L k =(L1∈Area k )∪((vx,vy)∈L4∈Area k and min d (vx,vy)>θ3) Among them, (x k ,y k )∈L k represent the longitude and latitude of all transmitting locations contained in area k, L k Contains all real launch positions and virtual launch positions that meet the conditions in area k; Step 1.11: Create a regional geographic information-launch location list mapping: f5: A→L Among them, f5 represents the function that maps the elements in set A to the elements in set L. Represents all regional geographic information, represents the set of all launch locations, p is the total number of regions, (x, y)∈L represents the longitude and latitude of the launch location respectively; Create a mapping between regional geographic information, launch location list, and type list: Step 1.12: Combining the real launch location-type list mapping obtained in step 1.1, the virtual launch location-type list mapping obtained in step 1.7, and the regional geographic information-launch location list mapping obtained in step 1.11, a regional geographic information-launch location list-type list mapping can be finally established; If in step 1.10, a virtual launch position coincides with a real launch position, then extract the types that are not in the real launch position from the target type list of the virtual launch position, and add these types to the real launch position-type list mapping established in step 1.1; combine the virtual launch position-type list mapping obtained in step 1.7 with the supplemented real launch position-type list mapping, correspond all types to the set L of all launch positions obtained in step 1.11, and establish a launch position-type list mapping: f6: L→M Wherein, f6 represents a function that maps elements in set L to elements in set M, and M=M1UM4 is a set of lists of all types; Step 1.13: Combine the regional geographic information-transmission location list mapping obtained in step 1.11 with the transmission location-type list mapping obtained in step 1.12 to establish a regional geographic information-transmission location list-type list mapping: f7: A→L→M Among them, f7 is a composite mapping function from set A to set L, and then from set L to set M.

7. The infrared target type recognition device guided by emission position sampling matching according to claim 6 is characterized in that: The implementation of the transmit position estimation module includes the following steps: Step 2.1: Calculate the launch time t of target o o : t o = inf{t o |E o (t) = Fitting(T o , E o )<θ1}, where T o 、E o Respectively represent the time variation information and energy variation information of the target o, Fitting(T o , E o ) indicates that T o The horizontal axis E o Fitting is done for the vertical axis, inf represents the first value that meets the requirements, t o According to T o and E o The fitting relationship predicts the time forward until the energy is less than the threshold θ1; Step 2.2: Calculate the longitude x of the target launch point o and latitude y o : x o ={λ o (t o )|λ o (t)=Fitting(T o ,λ o )} Among them, λ o , They respectively represent the longitude change information and latitude change information of the target o.

8. The infrared target type recognition method based on emission position guided sampling matching according to claim 7 is characterized in that: The implementation of the type identification module includes the following steps: Step 3.1: Based on all the regional geographic information A obtained in step 1.11, obtain the longitude and latitude (x o ,y o )Area List A((x o ,y o )): Step 3.2: According to the regional geographic information-transmission location list mapping in the regional geographic information-transmission location list-type list mapping established in step 1.13, obtain (x o ,y o ) corresponds to the launch position list L((x o ,y o )): L((x o ,y o ))=f7(A((x o ,y o )))→Lwhere (ox,oy)∈L((x o ,y o )) respectively represent (x o ,y o ) corresponds to the longitude and latitude of the transmitting location in the area to which it belongs; Step 3.3: Calculate (x o ,y o ) and the corresponding launch position list L((x o ,y o )) and sort the launch positions from small to large distances to obtain a list of sorted launch positions L S ((x o ,y o )): L S ((x o ,y o ))=Sort((kx,ky)|(kx,ky)∈L((x o ,y o )),d((x o ,y o ),(kx,ky))) Among them, (sx,sy)∈L S ((x o ,y o )) respectively represent the L((x o ,y o )) After sorting, the longitude and latitude of the launch position; Step 3.4: According to the sorted launch position list L S ((x o ,y o ), combined with the launch location list-type list mapping in the regional geographic information-launch location list-type list mapping established in step 1.13, we get (x o ,y o ) corresponds to the type vector M((x o ,y o )): M((x o ,and o ))=f7(L S ((x o ,and o )))→M M((x o ,y o )) contains (x o ,y o ) After sorting the area to which it belongs, all types contained in all emission positions are obtained to achieve global type matching template sampling; Step 3.5: Based on the type vector obtained in step 3.4, use the type matching algorithm from top to bottom to calculate the target o and the type vector M((x o ,y o )) and select the type Model(o) with the highest similarity as the type of target o to achieve infrared target type recognition: Among them, S(o,mdl) represents the type matching algorithm used to calculate the target o and M((x o ,y o )) in type mdl.

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