Single-antenna satellite velocity measurement method and system for two-dimensional ballistic correction fuses

Abstract

This invention discloses a single-antenna satellite velocity measurement method and system for two-dimensional ballistic correction fuses, which can be used to measure the velocity of satellite signals received by a single antenna in a two-dimensional ballistic correction fuse. It includes several functional modules: a roll attitude measurement module, a positioning module, a neural network rotating Doppler prediction module, a rotating Doppler stripping velocity measurement module, and a satellite signal baseband tracking processing module. The single-patch microstrip antenna mounted on the side of a two-dimensional ballistic correction fuse suffers from severe rotating Doppler interference in the carrier Doppler frequency formed by receiving satellite signals during rotation, and the interference mechanism is complex, making accurate velocity measurement difficult. This invention proposes a velocity measurement method for single-antenna rotating satellite signal reception, utilizing a neural network to strip the rotating Doppler component from the carrier Doppler, thereby achieving accurate velocity measurement.

Description

Technical Field

[0001] This invention relates to the field of satellite signal processing technology, and in particular to a single-antenna satellite velocity measurement method and system for two-dimensional ballistic correction fuses. Background Technology

[0002] The carrier Doppler frequency of the two-dimensional ballistic correction fuze, which receives satellite signals during rotation, is severely affected by rotating Doppler interference, and the mechanism of this interference is complex, making it difficult to achieve accurate velocity measurement.

[0003] The existing solution involves mounting an omnidirectional antenna at the front of the fuze. When the projectile rotates the fuze, the omnidirectional antenna, due to its omnidirectional characteristics, does not produce rotational Doppler modulation. Utilizing a single antenna mounted on the side of the cylindrical part of the fuze to receive satellite signals has the advantages of small antenna size, low cost, and simple structure. It can also realize roll attitude measurement based on satellite signals, making it necessary to study navigation and velocity measurement functions under this mounting method.

[0004] When receiving satellite signals using a single side antenna, the rotating Doppler frequency is modulated. The velocity measurement results obtained using the Doppler velocity measurement principle have a large error, and there is currently no solution to this problem. Summary of the Invention

[0005] In view of this, the present invention provides a single-antenna satellite velocity measurement method and system for a two-dimensional ballistic correction fuze, which can establish a predictive relationship between the rotating Doppler component in the carrier Doppler and the rotational speed, rotation angle and relative position, strip the rotating Doppler frequency, and use the carrier frequency after the rotating Doppler stripping for velocity measurement, thereby realizing accurate velocity measurement of rotating satellite signals.

[0006] To achieve the above objectives, the technical solution of the present invention is: a single-antenna satellite velocity measurement method for a two-dimensional ballistic correction fuze, comprising the following steps:

[0007] A Doppler recognition network based on a neural network structure is constructed. The input layer nodes of the Doppler recognition network consist of the antenna roll angle and rotation speed, and the satellite line-of-sight unit vector. The output layer of the Doppler recognition network has one node, which is the rotational Doppler frequency shift. The constructed Doppler recognition network is then trained.

[0008] It receives satellite signals, performs baseband tracking processing on the satellite signals, and obtains the carrier measurement frequency.

[0009] The antenna roll angle and rotation speed were measured.

[0010] Positioning is performed against a satellite to obtain the satellite line-of-sight unit vector.

[0011] The rotational Doppler frequency shift is estimated using a trained Doppler recognition network, and rotational correlated Doppler stripping is performed based on the carrier measurement frequency.

[0012] Accurate velocity measurement is performed based on the Doppler frequency after stripping using rotating Doppler stripping, and the final velocity measurement result is obtained.

[0013] Furthermore, the satellite line-of-sight unit vector is obtained by positioning the satellite. Specifically, the obtained satellite line-of-sight unit vector is (a x ,a y ,a z The x, y, and z axes are the coordinate axes of the geocentric geofixed coordinate system.

[0014] For satellite i, its line-of-sight unit vector is The calculation formula is as follows:

[0015]

[0016] in (x, y, z) represents the position coordinates of satellite i in the geocentric coordinate system, (x, y, z) represents the positioning result of the satellite receiver, and r represents the relative distance between the satellite and the user.

[0017] Furthermore, a Doppler recognition network based on a neural network structure is constructed, specifically as follows:

[0018] The input layer of the neural network has five nodes: including rotation speed and rotation angle information. γ T Satellite line-of-sight unit vector in geocentric and geofixed coordinate system (a) x ,a y ,a z );γ T This refers to the antenna roll angle towards the sky. Let the rotational speed be the input variable of the neural network; then the input variable is represented as:

[0019] The output layer of the neural network has one node, which is a rotational Doppler shift.

[0020] There are a total of 4 hidden layer nodes in the neural network, V1 to V4.

[0021] Set the weights from input layer nodes to hidden layer nodes, the threshold for hidden layer nodes, the weights from hidden layer nodes to output layer nodes, and the threshold for output layer nodes.

[0022] Set the transfer function from the input layer to the hidden layer and from the hidden layer to the output layer to the Sigmoid activation function.

[0023] Furthermore, based on the Doppler frequency after stripping, a precise velocity measurement was performed after rotating Doppler stripping to obtain the final velocity measurement result, specifically:

[0024] Solving the velocity equation yields the velocity. The velocity equation for satellite i is:

[0025]

[0026] in, The Doppler frequency after satellite i is stripped; It is the Doppler frequency generated by the translational motion of satellite i. It is a known quantity obtained through ephemeris; These are the components of satellite i's translational velocity along each axis in the geocentric Earth-fixed coordinate system. It is a known quantity obtained through ephemeris; v x ,v y ,v z The velocity of the carrier is an unknown quantity; t d It is a drifting clock, belonging to the unknown quantity.

[0027] By combining velocity equations from multiple satellites and performing a least-squares solution, the velocity (v) of the carrier can be calculated through a combination of velocity equations from four or more satellites. x ,v y ,v z ) and t d The solution to Zhong Piao's problem.

[0028] Another embodiment of the present invention provides a single-antenna satellite velocity measurement system for a two-dimensional ballistic correction fuze, including a roll attitude measurement module, a positioning module, a neural network rotating Doppler recognition module, a rotating Doppler stripping velocity measurement module, and a satellite signal baseband tracking processing module.

[0029] The satellite signal baseband tracking processing module receives satellite signals, performs baseband tracking processing on the satellite signals, obtains the carrier measurement frequency, and sends it to the neural network rotating Doppler recognition module.

[0030] The roll attitude measurement module measures the rotation speed and angle information and sends it to the neural network rotation Doppler recognition module.

[0031] The positioning module obtains the satellite line-of-sight unit vector and sends it to the neural network rotational Doppler recognition module.

[0032] The neural network rotational Doppler identification module includes a Doppler identification network based on a neural network structure. The Doppler identification network's input layer nodes consist of the antenna roll angle and rotation speed, and the satellite line-of-sight unit vector. The output layer of the Doppler identification network has only one node, which is the rotational Doppler frequency shift. After the Doppler identification network is trained, it constructs an input vector using the rotation speed and roll angle information from the roll attitude measurement module and the satellite line-of-sight unit vector from the positioning module to estimate the rotational Doppler frequency shift. Based on the output of the Doppler identification network and combined with the carrier measurement frequency, the neural network rotational Doppler identification module performs rotation-related Doppler stripping.

[0033] Based on the carrier frequency, the rotational speed and angle information obtained from the roll attitude measurement module, and the satellite line-of-sight unit vector obtained from the positioning module, rotation-related Doppler identification is performed. Then, rotation-related Doppler stripping is performed on the carrier frequency, and the stripped Doppler frequency is input into the rotation-related Doppler stripping velocity measurement module.

[0034] The rotating Doppler stripping velocimetry module is used to accurately measure the velocity after rotating Doppler stripping based on the Doppler frequency after stripping, and finally obtain the velocity measurement result.

[0035] Furthermore, the output of the satellite signal baseband tracking processing module is the carrier measurement frequency. i represents the satellite number; the rotational speed and rotational angle information obtained from the roll attitude measurement module are respectively... γ T γ T This refers to the antenna roll angle towards the sky. The rotational speed is given by the positioning module; the satellite line-of-sight unit vector obtained by the positioning module is (a x ,a y ,a z The x, y, and z axes are the coordinate axes of the geocentric Earth-fixed coordinate system; the Doppler frequency after stripping is...

[0036] The speed measurement result is v k .

[0037] The neural network rotation Doppler recognition module uses a neural network structure, with five input layer nodes: including rotation speed and rotation angle information. γ T Satellite line-of-sight unit in geocentric and geofixed coordinate system; position vector (a) x ,a y ,a z The input variables of a neural network are represented as follows:

[0038] There is one node in the output layer, which is a rotating Doppler frequency shift.

[0039] There are 4 hidden layer nodes in total, V1 to V4 are hidden layer nodes.

[0040] Set the weights from input layer nodes to hidden layer nodes, the threshold for hidden layer nodes, the weights from hidden layer nodes to output layer nodes, and the threshold for output layer nodes.

[0041] Furthermore, the rotating Doppler stripping velocimetry module obtains the velocity using the velocimetry equation. In the rotating Doppler stripping velocimetry module, the velocity is obtained by solving the velocimetry equation. The velocimetry equation for satellite i is:

[0042]

[0043] in, The Doppler frequency after satellite i is stripped; It is the Doppler frequency generated by the translational motion of satellite i. It is a known quantity obtained through ephemeris; These are the components of satellite i's translational velocity along each axis in the geocentric Earth-fixed coordinate system. It is a known quantity obtained through ephemeris; v x ,v y ,v z The velocity of the carrier is an unknown quantity; t d It's a time of drifting, belonging to the unknown quantity;

[0044] By combining velocity equations from multiple satellites and performing a least-squares solution, the velocity (v) of the carrier can be calculated through a combination of velocity equations from four or more satellites. x ,v y ,v z ) and t d The solution to Zhong Piao's problem.

[0045] Beneficial effects:

[0046] This invention designs a velocity measurement system and method for single-antenna rotating reception of satellite signals. By analyzing the influence of projectile rotation speed, rotation angle, and the relative positional relationship between the projectile and the satellite on the rotating Doppler frequency, a neural network is constructed to establish a predictive relationship between the rotating Doppler component in the carrier Doppler and the rotation speed, rotation angle, and relative position. The rotating Doppler frequency is then stripped, and the velocity is measured using the carrier frequency after the rotating Doppler is stripped. This invention can achieve accurate velocity measurement of satellite signals received by a single-antenna rotating receiver using a two-dimensional ballistic correction fuze. Attached Figure Description

[0047] Figure 1 A block diagram of a single-antenna velocity measurement system for a two-dimensional ballistic correction fuze provided by the present invention;

[0048] Figure 2 This is a schematic diagram of the rotational Doppler estimation network structure based on a neural network. Detailed Implementation

[0049] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0050] This invention provides a single-antenna satellite velocity measurement method for a two-dimensional ballistic correction fuze, comprising the following steps:

[0051] Step 1: Construct a Doppler recognition network based on a neural network structure. The Doppler recognition network consists of the antenna roll angle and rotation speed, and the satellite line-of-sight unit vector as the input layer nodes. The Doppler recognition network has one output layer node, which is the rotational Doppler frequency shift.

[0052] The Doppler recognition network based on a neural network structure constructed in this step has the following structure: Figure 2 As shown, specifically:

[0053] The input layer of the neural network has five nodes: including rotation speed and rotation angle information. γ T Satellite line-of-sight unit vector in geocentric and geofixed coordinate system (a) x ,a y ,a z );γ T This refers to the antenna roll angle towards the sky. Let the rotational speed be the input variable of the neural network; then the input variable is represented as:

[0054] The output layer of the neural network has one node, which is a rotational Doppler frequency shift.

[0055] There are a total of 4 hidden layer nodes in the neural network, V1 to V4 are hidden layer nodes;

[0056] Set the weights from input layer nodes to hidden layer nodes, the thresholds for hidden layer nodes, the weights from hidden layer nodes to output layer nodes, and the thresholds for output layer nodes;

[0057] Set the transfer function from the input layer to the hidden layer and from the hidden layer to the output layer to the sigmoid activation function, that is:

[0058]

[0059] The constructed Doppler recognition network is trained; the rotating Doppler frequencies of all satellite signals received in multiple experiments are used as a dataset, and the neural network is trained extensively to obtain more accurate prediction coefficients.

[0060] Step 2: Receive satellite signals, perform baseband tracking processing on the satellite signals, and obtain the carrier measurement frequency; measure the antenna roll angle and rotation speed.

[0061] The satellite line-of-sight unit vector is obtained by positioning the satellite; in this embodiment of the invention, the obtained satellite line-of-sight unit vector is (a x ,a y ,a z The x, y, and z axes are the coordinate axes of the geocentric geofixed coordinate system.

[0062] For satellite i, its line-of-sight unit vector is The calculation formula is as follows:

[0063]

[0064] in (x, y, z) represents the position coordinates of satellite i in the geocentric coordinate system, (x, y, z) represents the positioning result of the satellite receiver, and r represents the relative distance between the satellite and the user.

[0065] Step 3: Estimate the rotational Doppler frequency shift using the trained Doppler recognition network, and perform rotational correlated Doppler stripping based on the carrier measurement frequency; in this embodiment of the invention, the rotational Doppler frequency is obtained using a neural network-based rotational Doppler prediction module. Then, it was separated from the measured Doppler frequencies.

[0066] Step 4: Perform precise velocity measurement based on the stripped Doppler frequency using rotating Doppler stripping to obtain the final velocity measurement result. This step involves performing precise velocity measurement based on the stripped Doppler frequency using rotating Doppler stripping to obtain the final velocity measurement result, specifically as follows:

[0067] Solving the velocity equation yields the velocity. The velocity equation for satellite i is:

[0068]

[0069] in, The Doppler frequency after satellite i is stripped; It is the Doppler frequency generated by the translational motion of satellite i. It is a known quantity obtained through ephemeris; These are the components of satellite i's translational velocity along each axis in the geocentric Earth-fixed coordinate system. It is a known quantity obtained through ephemeris; v x ,v y ,v z The velocity of the carrier is an unknown quantity; t d It's a time of drifting, belonging to the unknown quantity;

[0070] By combining velocity equations from multiple satellites and performing a least-squares solution, the velocity (v) of the carrier can be calculated through a combination of velocity equations from four or more satellites.x ,v y ,v z ) and t d The solution to Zhong Piao's problem.

[0071] Figure 2 This is a block diagram of a single-antenna velocity measurement method for a two-dimensional ballistic correction fuze designed in this invention, which includes the following components: a roll attitude measurement module 1, a positioning module 2, a neural network rotating Doppler recognition module 3, a rotating Doppler stripping velocity measurement module 4, and a satellite signal baseband tracking processing module 5.

[0072] The satellite signal is input into the satellite signal baseband tracking processing module 5 to obtain the carrier measurement frequency. Neural network rotating Doppler recognition module 3 based on carrier frequency The rotational speed and rotational angle information obtained by the roll attitude measurement module (1) γ T And the satellite line-of-sight unit vector (a) obtained by the positioning module. x ,a y ,a z Rotational correlation Doppler stripping was performed, and the Doppler frequencies after stripping were determined. The data is input into the rotating Doppler stripping velocimetry module 4 to achieve accurate velocimetry after rotating Doppler stripping, ultimately obtaining the velocity v. k .

[0073] The basic principle block diagram of the neural network rotational Doppler recognition module 3 is as follows: Figure 1 As shown. Input variables include rotational speed, rotation angle, and the satellite line-of-sight unit vector in projectile coordinates. The output layer has 1 neuron and is a rotational Doppler shift. Input variables are represented as follows:

[0074]

[0075] γ T This refers to the antenna roll angle towards the sky. For rotational speed, (a x ,a y ,a z Let ) be the line-of-sight vector (LOS) between satellite j and the user, and its calculation formula is:

[0076]

[0077] (x, y, z) represents the position of satellite i, (x, y, z) represents the positioning result, and r represents the relative distance between the satellite and the user. Figure 1 In the input layer, there are n=5 nodes, including the rotation speed, rotation angle, and relative position vector; the output layer has m=1 nodes, which is the Doppler frequency shift caused by rotation; V jThere are 4 hidden layer nodes. The weight from the input layer node to the hidden layer node is ω. ij The threshold for hidden layer nodes is α. i The weight from the hidden layer to the output layer node is ω. jk The threshold for the output layer nodes is β. k The transfer functions from the input layer to the hidden layer and from the hidden layer to the output layer use the sigmoid activation function, i.e.:

[0078]

[0079] The rotational Doppler frequency is obtained using a neural network-based rotational Doppler prediction module. Then, it was separated from the measured Doppler frequencies. Finally, the velocity can be obtained by solving the velocity measurement equation through the rotating Doppler stripping velocity measurement module (4), and the calculation formula is as follows:

[0080]

[0081] in, It is the Doppler frequency generated by the translational motion of satellite i, a known quantity obtained through ephemeris analysis. It is the translational velocity of satellite i, which is also a known quantity obtained through ephemeris, (v x ,v y ,v z ) represents the velocity of the carrier, t d This is clock drift, which is an unknown quantity. Using the above formula and performing a least-squares solution, the carrier's velocity (v) can be obtained using at least four satellites. x ,v y ,v z ) and t d The solution to Zhong Piao's problem.

[0082] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A single antenna satellite velocity measurement method for two dimensional ballistic correction fuze, characterized in that, Includes the following steps: A Doppler recognition network based on a neural network structure is constructed. The input layer nodes of the Doppler recognition network consist of antenna roll angle and rotation speed, and satellite line-of-sight unit vector. The output layer of the Doppler recognition network has one node, which is the rotational Doppler frequency shift. The constructed Doppler recognition network is then trained. Receive satellite signals, perform baseband tracking processing on the satellite signals, and obtain the carrier measurement frequency; The antenna roll angle and rotational speed were measured. The satellite is positioned to obtain a satellite line-of-sight unit vector, and specifically, the obtained satellite line-of-sight unit vector is x, y and z axes are coordinate axes of an earth-centered and earth-fixed coordinate system. For satellite i, its satellite line-of-sight unit vector is The calculation formula is: in These are the position coordinates of satellite i in the Earth-centered Earth-fixed coordinate system. This is the positioning result from the satellite receiver, where r is the relative distance between the satellite and the user; The rotational Doppler frequency shift is estimated using a trained Doppler recognition network, and rotational correlated Doppler stripping is performed based on the carrier measurement frequency. Based on the Doppler frequency after stripping, a precise velocity measurement is performed after rotating Doppler stripping to obtain the final velocity measurement result, as follows: Solving the velocity equation yields the velocity. The velocity equation for satellite i is: in, For satellite i Doppler frequencies after stripping; It is a satellite i Doppler frequency generated by translation; It is a satellite i The translational velocity components along each axis in the geocentric geofixed coordinate system; The speed of the carrier's movement; He is a drifter in Zhong; By combining velocity equations from multiple satellites and performing a least-squares solution, the velocity of the carrier can be calculated using a combination of velocity equations from four or more satellites. and The solution to Zhong Piao's problem.

2. The single-antenna satellite velocity measurement method for a two-dimensional ballistic correction fuze as described in claim 1, characterized in that, The construction of the Doppler recognition network based on a neural network structure is specifically as follows: The input layer of the neural network has five nodes: including rotation speed and rotation angle information. Satellite line-of-sight unit vector in geocentric and geofixed coordinate system The input variables of the neural network are then represented as: ; The output layer of the neural network has one node, which is a rotational Doppler frequency shift. There are a total of 4 hidden layer nodes in the neural network. For hidden layer nodes; Set the weights from input layer nodes to hidden layer nodes, the thresholds for hidden layer nodes, the weights from hidden layer nodes to output layer nodes, and the thresholds for output layer nodes; Set the transfer function from the input layer to the hidden layer and from the hidden layer to the output layer to the Sigmoid activation function.

3. A single-antenna satellite velocity measurement system for a two-dimensional ballistic correction fuze, characterized in that, It includes a roll attitude measurement module (1), a positioning module (2), a neural network rotational Doppler recognition module (3), a rotational Doppler stripping velocity measurement module (4), and a satellite signal baseband tracking processing module (5); The satellite signal baseband tracking processing module (5) receives the satellite signal, performs baseband tracking processing on the satellite signal, obtains the carrier measurement frequency, and sends it to the neural network rotating Doppler recognition module (3). The rolling attitude measurement module (1) measures the rotation speed and rotation angle information and sends it to the neural network rotation Doppler recognition module (3). The positioning module (2) obtains the satellite line-of-sight unit vector and sends it to the neural network rotation Doppler recognition module (3). The neural network rotational Doppler identification module (3) includes a Doppler identification network based on a neural network structure. The Doppler identification network consists of input layer nodes composed of antenna roll angle and rotation speed, and satellite line-of-sight unit vector. The output layer of the Doppler identification network has one node, which is the rotational Doppler frequency shift. After the Doppler identification network is trained, it constructs an input vector using the rotation speed and angle information from the roll attitude measurement module (1) and the satellite line-of-sight unit vector from the positioning module (2) to estimate the rotational Doppler frequency shift. The neural network rotational Doppler identification module (3) performs rotation-related Doppler stripping based on the output of the Doppler identification network and the carrier measurement frequency. Based on the carrier measurement frequency, the rotational speed and angle information obtained by the roll attitude measurement module (1), and the satellite line-of-sight unit vector obtained by the positioning module (2), rotational related Doppler identification is performed, and then rotational related Doppler stripping is performed on the carrier measurement frequency. The stripped Doppler frequency is input into the rotational Doppler stripping velocity measurement module (4). The rotating Doppler stripping velocimetry module (4) is used to achieve accurate velocimetry after rotating Doppler stripping based on the Doppler frequency after stripping, and finally obtain the velocimetry result; The output of the satellite signal baseband tracking processing module (5) is the carrier measurement frequency. , i is the satellite number; the rotational speed and rotational angle information obtained by the roll attitude measurement module (1) are respectively The satellite line-of-sight unit vector obtained by the positioning module is: The x, y, and z axes are the coordinate axes of the geocentric Earth-fixed coordinate system; the Doppler frequency after stripping is... ; Speed ​​measurement results are ; The neural network rotation Doppler recognition module (3) is a neural network structure. The neural network has five input layer nodes, including rotation speed and rotation angle information. Satellite line-of-sight unit vector in geocentric and geofixed coordinate system The input variables of a neural network are represented as follows: ; The output layer has one node, which is a rotating Doppler frequency shift; There are 4 hidden layer nodes in total. For hidden layer nodes; Set the weights from input layer nodes to hidden layer nodes, the thresholds for hidden layer nodes, the weights from hidden layer nodes to output layer nodes, and the thresholds for output layer nodes; The rotating Doppler stripping velocimetry module (4) obtains the motion velocity using a velocimetry equation. In the rotating Doppler stripping velocimetry module (4), the motion velocity is obtained by solving the velocimetry equation. The velocimetry equation for satellite i is: in, For satellite i Doppler frequencies after stripping; It is a satellite i Doppler frequency generated by translation; It is a satellite i The translational velocity components along each axis in the geocentric geofixed coordinate system; The velocity of the carrier. He is a drifter in Zhong; By combining velocity equations from multiple satellites and performing a least-squares solution, the velocity of the carrier can be calculated using a combination of velocity equations from four or more satellites. and The solution to Zhong Piao's problem.

Images