A multi-mode fusion tracking and positioning method for low-altitude targets

Abstract

The present invention provides a multi-mode fusion tracking and positioning method for low-altitude targets, which can be applied to the field of target tracking and detection technology. The method includes: using a multi-mode fusion lidar to perform infrared tracking and single-photon laser ranging on a low-altitude target to obtain the angle information, real-time pointing information, and real-time distance information of the low-altitude target; performing operations on the angle information and the real-time pointing information to obtain the real-time azimuth information and real-time pitch angle information of the low-altitude target, and constructing a real-time measurement vector of the low-altitude target by using the real-time azimuth information, real-time pitch angle information, and real-time distance information; defining a target state vector of a variable-speed second-order motion model of the low-altitude target by using the real-time measurement vector; using a Kalman filter to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector to obtain a target state estimation vector of the low-altitude target, and performing three-dimensional tracking and positioning on the low-altitude target by using the target state estimation vector.

Description

Technical Field

[0001] The present invention relates to the technical field of target tracking and detection, and particularly to a multi-modal fusion tracking and positioning method, an electronic device, and a storage medium for low-altitude targets. Background Art

[0002] In recent years, with the booming development of the low-altitude economy and the rapid popularization of unmanned aerial vehicle (UAV) technology, the wide application of UAVs in fields such as logistics, agriculture, and emergency rescue has created remarkable value for society. Low-altitude targets represented by small UAVs have characteristics such as small size, low flight altitude, and strong mobility. Their reflected signals are weak and vulnerable to complex environmental interference, posing unprecedented challenges to traditional monitoring technologies.

[0003] In existing detection technologies, radar, as an active detection means, realizes target recognition by transmitting electromagnetic waves and receiving target reflected signals. However, its effectiveness in the low-altitude environment is significantly limited. Background clutter such as dense buildings and complex terrain in the low-altitude area will interfere with radar beams, resulting in target signals being covered by noise. At the same time, the radar cross-section of small UAVs is extremely low, and traditional radar systems are difficult to effectively separate target signals from clutter, leading to a significant reduction in the detection probability. Infrared imaging technology realizes passive detection based on the thermal radiation characteristics of targets. Although it can avoid electromagnetic interference problems, it is difficult to support precise positioning because it cannot directly obtain distance parameters. Traditional lidar has high-precision ranging ability, but its narrow field of view limits the search coverage range and is difficult to meet the requirements of large-scale dynamic monitoring. In addition, the low sensitivity of traditional detection means and the attenuation effect of laser in atmospheric transmission limit the detection distance of traditional lidar for small targets to a few kilometers, further weakening its practicality. Summary of the Invention

[0004] In view of the above problems, the present invention provides a multi-modal fusion tracking and positioning method, an electronic device, and a storage medium for low-altitude targets, which are used to solve at least one of the existing technical problems.

[0005] According to the first aspect of the present invention, a multi-modal fusion tracking and positioning method for low-altitude targets is provided, including:

[0006] Using a multi-modal fusion lidar to perform infrared tracking and single-photon laser ranging on a low-altitude target, obtaining the angle information, real-time pointing information, and real-time distance information of the low-altitude target. Among them, the above multi-modal fusion lidar includes a passive detection type infrared guiding module, a single-photon laser emitting module, a single-photon laser detecting module, a pointing module, and an electronics module;

[0007] The angular information and real-time pointing information are calculated to obtain the real-time azimuth angle information and real-time elevation angle information of the low-altitude target, and the real-time measurement vector of the low-altitude target is constructed by using the real-time azimuth angle information, real-time elevation angle information, and real-time distance information;

[0008] The target state vector of the variable-speed second-order motion model of the low-altitude target is defined by using the real-time measurement vector;

[0009] The Kalman filter is used to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector to obtain the target state estimation vector of the low-altitude target, and the three-dimensional tracking and positioning of the low-altitude target is performed by using the target state estimation vector.

[0010] According to an embodiment of the present invention, the infrared tracking and single-photon laser ranging of the low-altitude target by using the multi-mode fusion radar of the low-altitude target to obtain the angular information, real-time pointing information, and real-time distance information of the low-altitude target include:

[0011] The passive detection type infrared guidance module is used to perform infrared tracking on the low-altitude target to obtain the infrared image of the low-altitude target, and the angular information of the low-altitude target is obtained by performing image processing on the infrared image, wherein the angular information includes the azimuth angle miss distance and the elevation angle miss distance;

[0012] The pointing module is used to obtain the real-time pointing information of the low-altitude target, and the single-photon laser emission module and the single-photon laser detection module are used to collect the real-time distance information and real-time signal-to-noise ratio information of the low-altitude target.

[0013] According to an embodiment of the present invention, the calculation of the angular information and the real-time pointing information to obtain the real-time azimuth angle information and real-time elevation angle information of the low-altitude target includes:

[0014] The azimuth angle in the real-time pointing information and the azimuth angle miss distance are calculated to obtain the real-time azimuth angle information, and the elevation angle in the real-time pointing information and the elevation angle miss distance are calculated to obtain the real-time elevation angle information.

[0015] According to an embodiment of the present invention, the definition of the target state vector of the variable-speed second-order motion model of the low-altitude target by using the real-time measurement vector includes:

[0016] The first-order derivative vector and the second-order derivative vector of the real-time measurement vector are calculated, and the target state vector is constructed by using the real-time measurement vector, the first-order derivative vector of the real-time measurement vector, and the second-order derivative vector of the real-time measurement vector;

[0017] The state transition matrices of the real-time measurement vector, the first-order derivative vector of the real-time measurement vector, and the second-order derivative vector of the real-time measurement vector are calculated respectively by using the variable-speed second-order motion model of the low-altitude target;

[0018] The overall state transition matrix of the low-altitude target is formed by the state transition matrix of the real-time measurement vector, the state transition matrix of the first-order derivative vector of the real-time measurement vector, and the state transition matrix of the second-order derivative vector of the real-time measurement vector in a block diagonal matrix form.

[0019] According to an embodiment of the present invention, the above-mentioned state prediction processing and state update processing are alternately and iteratively performed on the target state vector and the real-time measurement vector by using the Kalman filter to obtain the target state estimation vector of the low-altitude target, including:

[0020] Construct the target state estimation vector at the current moment by using the overall state transition matrix of the low-altitude target and the target state estimation vector filtered by the Kalman filter at the previous moment;

[0021] Construct the error covariance matrix at the current moment by using the overall state transition matrix of the low-altitude target, the process noise covariance matrix, and the error covariance matrix at the previous moment, thereby completing the state prediction processing of the Kalman filter, where the error covariance matrix is used for state update estimation.

[0022] According to an embodiment of the present invention, the above-mentioned state prediction processing and state update processing are alternately and iteratively performed on the target state vector and the real-time measurement vector by using the Kalman filter to obtain the target state estimation vector of the low-altitude target further including:

[0023] Obtain the observation noise covariance matrix that can be adaptively adjusted at the current moment by using the real-time signal-to-noise ratio information at the current moment, the basic observation noise covariance matrix, and the preset adjustment coefficient, and obtain the observation noise at the current moment based on the observation noise covariance matrix at the current moment;

[0024] Construct the measurement model at the current moment by using the observation noise, the measurement matrix, and the target state estimation vector at the current moment, and perform state update processing on the target state estimation vector at the current moment by using the measurement model at the current moment.

[0025] According to an embodiment of the present invention, the above-mentioned state update processing of the target state estimation vector at the current moment by using the measurement model at the current moment includes:

[0026] Perform an operation on the measurement model and the target state estimation vector at the current moment to obtain the residual vector at the current moment;

[0027] Perform an operation on the error covariance matrix, the measurement matrix, and the observation noise covariance matrix at the current moment to obtain the residual covariance at the current moment;

[0028] Calculate the Kalman gain at the current moment by using the error covariance matrix, the measurement matrix, and the residual covariance at the current moment;

[0029] Perform state update processing on the target state estimation vector at the current moment using the Kalman gain and residual vector at the current moment, and update the error covariance matrix at the current moment.

[0030] The second aspect of the present invention provides a multi-mode fusion tracking and positioning system for low-altitude targets, including:

[0031] A flight data acquisition module, configured to perform infrared tracking and single-photon laser ranging on a low-altitude target using a multi-mode fusion lidar to obtain the angle information, real-time pointing information, and real-time distance information of the low-altitude target. The multi-mode fusion lidar includes a passive detection type infrared guiding module, a single-photon laser emission module, a single-photon laser detection module, a pointing module, and an electronics module;

[0032] A flight data operation module, configured to perform operations on the angle information and real-time pointing information to obtain the real-time azimuth angle information and real-time pitch angle information of the low-altitude target, and construct a real-time measurement vector of the low-altitude target using the real-time azimuth angle information, real-time pitch angle information, and real-time distance information;

[0033] A target state quantity definition module, configured to define the target state vector of the variable-speed second-order motion model of the low-altitude target using the real-time measurement vector;

[0034] A three-dimensional tracking and positioning module, configured to perform state prediction processing and state update processing on the target state vector and the real-time measurement vector alternately using a Kalman filter to obtain the target state estimation vector of the low-altitude target, and perform three-dimensional tracking and positioning on the low-altitude target using the target state estimation vector.

[0035] The third aspect of the present invention provides an electronic device, including: one or more processors; a memory, configured to store one or more computer programs, wherein the above one or more processors execute the above one or more computer programs to implement the steps of the above method.

[0036] The fourth aspect of the present invention further provides a computer-readable storage medium, on which a computer program or instruction is stored, and when the above computer program or instruction is executed by a processor, the steps of the above method are implemented.

[0037] The multi-modal fusion tracking and positioning method for low-altitude targets provided by the present invention utilizes the high-sensitivity ranging ability of the multi-modal fusion lidar combined with the single-photon radar and the large field-of-view detection advantage of the infrared imaging, and can achieve high-precision three-dimensional positioning of low-altitude small targets. At the same time, a high-order motion model is adopted to predict the target trajectory, combined with multi-source data fusion, to ensure stable tracking even in the case of high-speed maneuvering of the target and complex trajectory changes. In addition, the system adopts infrared detection means and has a large field-of-view tracking ability to avoid the target leaving the field of view. Moreover, the data fusion weight is dynamically adjusted according to the signal-to-noise ratio of the single-photon radar to improve the utilization rate of high-signal-to-noise ratio data and reduce the impact of low-quality measurement data on the tracking accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Through the following description of the embodiments of the present invention with reference to the drawings, the above content and other objects, features and advantages of the present invention will become clearer. In the drawings:

[0039] Figure 1 is a flowchart of the multi-modal fusion tracking and positioning method for low-altitude targets according to an embodiment of the present invention;

[0040] Figure 2 is a schematic structural diagram of the multi-modal fusion lidar according to an embodiment of the present invention;

[0041] Figure 3 is a schematic diagram of multi-modal fusion tracking based on a Kalman filter according to an embodiment of the present invention;

[0042] Figure 4 is a schematic structural diagram of the multi-modal fusion tracking and positioning system for low-altitude targets according to an embodiment of the present invention;

[0043] Figure 5 is a block diagram of an electronic device suitable for implementing the multi-modal fusion tracking and positioning method for low-altitude targets according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, it should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present invention. However, obviously, one or more embodiments can be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0045] The terms used herein are merely for describing specific embodiments and are not intended to limit the present invention. The terms "comprising", "including" and the like used herein indicate the presence of the described features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components.

[0046] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0047] In the case of using expressions such as "at least one of A, B, and C, etc.", generally it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but not be limited to a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, C, etc.).

[0048] Due to the characteristics of low-altitude targets such as strong maneuverability, weak reflected signals, and low flight altitude, traditional monitoring technologies have technical problems such as high false alarm rates, insufficient tracking accuracy, and difficulty in achieving continuous and stable tracking. To solve one of the above technical problems, the present invention provides a multi-mode fusion tracking and positioning method for low-altitude targets, which can significantly improve the positioning accuracy and tracking robustness in complex scenarios through multi-sensor fusion and adaptive optimization. In addition, the above multi-mode fusion tracking and positioning method for low-altitude targets provided by the present invention constructs a multi-dimensional collaborative perception system by deeply integrating the ultra-high sensitivity detection ability of single-photon lidar and the wide-field monitoring advantage of infrared imaging systems. The single-photon lidar can achieve photon-level weak signal detection and still accurately capture the distance information of low-altitude targets in a strong background noise environment; the infrared imaging system relies on the large field-of-view characteristics to achieve rapid search and continuous trajectory tracking of targets. Through the adaptive multi-source data fusion algorithm and the closed-loop feedback mechanism, the system can dynamically optimize the sensor data weights and suppress environmental interference in real time, so as to achieve high-robustness tracking and sub-meter trajectory positioning accuracy of low-altitude targets in complex scenarios. This technical solution provides an innovative solution idea for low-altitude safety prevention and control.

[0049] The above multi-mode fusion tracking and positioning method for low-altitude targets provided by the present invention will be further described in detail below through specific embodiments or specific implementation manners in combination with the drawings.

[0050] Figure 1 is a flowchart of a multi-mode fusion tracking and positioning method for low-altitude targets according to an embodiment of the present invention.

[0051] AsFigure 1 As shown, the multi-mode fusion tracking and positioning method for low-altitude targets includes operations S110 to S140.

[0052] In operation S110, a multi-mode fusion laser radar is used to perform infrared tracking and single-photon laser ranging on a low-altitude target to obtain angle information, real-time pointing information, and real-time distance information of the low-altitude target.

[0053] According to an embodiment of the present invention, the above-mentioned multi-mode fusion laser radar includes a passive detection infrared guidance module, a single-photon laser emission module, a single-photon laser detection module, a pointing module and an electronics module.

[0054] The following is a specific implementation method and combined with the attached Figure 2 The multi-mode fusion laser radar provided by the present invention is further described in detail.

[0055] Figure 2 2 is a schematic structural diagram of a multi-mode fusion laser radar according to an embodiment of the present invention.

[0056] like Figure 2 As shown, the multi-mode fusion lidar consists of a passive infrared guidance module, a single-photon laser emission module, a single-photon laser detection module, a pointing module, and an electronics module. The infrared signal emitted by the passive infrared guidance module and the single-photon laser signal emitted by the single-photon laser emission module have the same sampling frequency. The laser emission module emits pulsed laser light to illuminate the target, providing the necessary illumination for subsequent detection. The single-photon detection module receives the laser signal diffusely reflected from the target to accurately locate the target. The passive infrared guidance module uses a passive detection method to receive infrared light signals radiated by the target, enabling rapid target detection and tracking. The electronics module processes and fuses data from the single-photon detection module and the passive infrared guidance module to extract target information. Based on the signal processing results, the pointing module quickly adjusts the system's direction to the target area to ensure continuous monitoring.

[0057] The multimodal fusion lidar provided by the present invention fuses the single-photon lidar data obtained by the single-photon lidar with the infrared imaging data obtained by the passive detection type infrared guidance module, and uses the multimodal data obtained by the fusion to perform tracking imaging on low-altitude targets or low-altitude small targets. The passive detection type infrared guidance module utilizes infrared imaging technology. With a large field of view and long-distance detection capabilities, infrared imaging technology can adapt to irregular maneuvering changes of movement; while the single-photon lidar, as a direct criterion for target tracking effect, relies on an active detection mechanism to obtain high-precision target distance information, and can provide key ranging feedback in complex environments, ensuring the tracking stability and anti-interference ability of the system. The fusion of the two gives full play to their respective advantages and has the same sampling frequency. Therefore, while improving the reliability of target detection, it enhances the stable tracking ability of the system in complex environments and can achieve multimodal fusion on the same sampling frequency scale. The target tracking process uses Kalman filtering for state estimation, and by fusing the measurement information from two different sensing modules, it realizes the accurate prediction of the UAV trajectory.

[0058] In operation S120, the angle information and the real-time pointing information are calculated to obtain the real-time azimuth information and the real-time elevation angle information of the low-altitude target, and the real-time measurement vector of the low-altitude target is constructed by using the real-time azimuth information, the real-time elevation angle information, and the real-time distance information.

[0059] Since the infrared signal and the single-photon laser signal emitted by the multimodal fusion lidar have the same sampling frequency, the above-mentioned azimuth information, elevation angle information, and distance information can be obtained in real time, and the information of these three variables is consistent on the time scale.

[0060] In operation S130, the target state vector of the variable-speed second-order motion model of the low-altitude target is defined by using the real-time measurement vector.

[0061] In operation S140, the Kalman filter is used to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector, obtain the target state estimation vector of the low-altitude target, and perform three-dimensional tracking and positioning on the low-altitude target by using the target state estimation vector.

[0062] The multi-modal fusion tracking and positioning method for low-altitude targets provided by the present invention utilizes the high-sensitivity ranging ability of the multi-modal fusion lidar combined with the single-photon radar and the large field-of-view detection advantage of infrared imaging to achieve high-precision three-dimensional positioning of low-altitude small targets. At the same time, a high-order motion model is used to predict the target trajectory, combined with multi-source data fusion, to ensure stable tracking even when the target maneuvers at high speed and the trajectory changes complexly. In addition, the system uses infrared detection means and has a large field-of-view tracking ability to avoid the target leaving the field of view. Moreover, the data fusion weight is dynamically adjusted according to the signal-to-noise ratio of the single-photon radar to improve the utilization rate of high signal-to-noise ratio data and reduce the impact of low-quality measurement data on the tracking accuracy.

[0063] According to an embodiment of the present invention, the above-mentioned infrared tracking and single-photon laser ranging of a low-altitude target using a multi-modal fusion radar for low-altitude targets to obtain the angle information, real-time pointing information, and real-time distance information of the low-altitude target include: using a passive detection type infrared guidance module to perform infrared tracking on the low-altitude target to obtain an infrared image of the low-altitude target, and through image processing of the infrared image, obtaining the angle information of the low-altitude target, where the angle information includes the azimuth angle miss distance and the pitch angle miss distance; using a pointing module to obtain the real-time pointing information of the low-altitude target, and using a single-photon laser emission module and a single-photon laser detection module to collect the real-time distance information and real-time signal-to-noise ratio information of the low-altitude target.

[0064] According to an embodiment of the present invention, the above-mentioned operation of the angle information and the real-time pointing information to obtain the real-time azimuth angle information and real-time pitch angle information of the low-altitude target includes: performing an operation on the azimuth angle in the real-time pointing information and the azimuth angle miss distance to obtain the real-time azimuth angle information, and performing an operation on the pitch angle in the real-time pointing information and the pitch angle miss distance to obtain the real-time pitch angle information.

[0065] The following further details the process of obtaining the angle information, real-time pointing information, and real-time distance information of the low-altitude target and calculating the real-time pitch angle information through specific embodiments.

[0066] The passive detection type infrared guidance module is responsible for collecting the angle information of the target, and obtaining the azimuth angle miss distance of the target through image processing and the pitch angle miss distance . At the same time, by obtaining the real-time pointing information (azimuth angle , pitch angle ) of the turntable, the real-time azimuth angle and pitch angle information (azimuth angle , pitch angle ) of the target are obtained. When the single-photon detection module obtains an accurate measurement value of the target distance through active ranging and feeds back the signal-to-noise ratio of the current measurement to reflect the reliability of the data.

[0067] According to an embodiment of the present invention, the target state vector for defining the variable-speed second-order motion model of the low-altitude target using the real-time measurement vector includes: calculating the first-order derivative vector and the second-order derivative vector of the real-time measurement vector, and constructing the target state vector by using the real-time measurement vector, the first-order derivative vector of the real-time measurement vector, and the second-order derivative vector of the real-time measurement vector; respectively calculating the state transition matrices of the real-time measurement vector, the first-order derivative vector of the real-time measurement vector, and the second-order derivative vector of the real-time measurement vector by using the variable-speed second-order motion model of the low-altitude target; and forming the overall state transition matrix of the low-altitude target in the form of a block diagonal matrix with the state transition matrix of the real-time measurement vector, the state transition matrix of the first-order derivative vector of the real-time measurement vector, and the state transition matrix of the second-order derivative vector of the real-time measurement vector.

[0068] The following further elaborates in detail the process of defining the target state vector for the variable-speed second-order motion model of the low-altitude target using the real-time measurement vector through specific embodiments.

[0069] Integrate the angle data obtained by infrared imaging with the distance data obtained by the single-photon radar to form a measurement vector , where represents the th moment; considering the maneuvering characteristics of the target, a variable-speed second-order motion model is used to model the target, and the target state vector is defined as a nine-dimensional vector , where , and respectively represent the angle and distance of the target, , and are the corresponding first-order derivatives (angular velocity and radial velocity), , and are the second-order derivatives (angular acceleration and radial acceleration). Since the azimuth angle, pitch angle, and distance are consistent on the time scale, the target state quantity can be defined by using the method of multi-order derivatives.

[0070] According to an embodiment of the present invention, the above-mentioned process of alternately and iteratively performing state prediction processing and state update processing on the target state vector and the real-time measurement vector by using the Kalman filter to obtain the target state estimation vector of the low-altitude target includes: constructing the target state estimation vector at the current moment by using the overall state transition matrix of the low-altitude target and the target state estimation vector filtered by the Kalman filter at the previous moment; constructing the error covariance matrix at the current moment by using the overall state transition matrix of the low-altitude target, the process noise covariance matrix, and the error covariance matrix at the previous moment, thereby completing the state prediction processing of the Kalman filter, where the error covariance matrix is used for state update estimation.

[0071] The process of obtaining the target state estimation vector of the above-mentioned low-altitude target will be further described in detail through specific embodiments below.

[0072] For any state component (which can represent , or ), within the discrete time step , the motion model is shown in formulas (1) to (3):

[0073] (1),

[0074] (2),

[0075] (3),

[0076] Where is the process noise, represents the state component at the th moment, represents the first derivative of the state component at the th moment, represents the second derivative of the state component at the th moment.

[0077] The state transition matrix of a single component is shown in formula (4)

[0078] (4),

[0079] And the overall state transition matrix at the th moment is composed of a block diagonal matrix formed by three .

[0080] According to an embodiment of the present invention, the above-mentioned use of the Kalman filter to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector to obtain the target state estimation vector of the low-altitude target further includes: obtaining the observation noise covariance matrix that can be adaptively adjusted at the current moment by using the real-time signal-to-noise ratio information, the basic observation noise covariance matrix, and the preset adjustment coefficient at the current moment, and obtaining the observation noise at the current moment based on the observation noise covariance matrix at the current moment; constructing the measurement model at the current moment by using the observation noise, the measurement matrix, and the target state estimation vector at the current moment, and performing state update processing on the target state estimation vector at the current moment by using the measurement model at the current moment.

[0081] When stopping tracking the low-altitude target or the low-altitude small target, the Kalman filter terminates operation.

[0082] According to an embodiment of the present invention, the state update process for the target state estimation vector at the current moment using the measurement model at the current moment includes: performing an operation on the measurement model at the current moment and the target state estimation vector to obtain the residual vector at the current moment; performing an operation on the error covariance matrix, measurement matrix, and observation noise covariance matrix at the current moment to obtain the residual covariance at the current moment; calculating the Kalman gain at the current moment using the error covariance matrix, measurement matrix, and residual covariance at the current moment; performing a state update process on the target state estimation vector at the current moment using the Kalman gain and residual vector at the current moment, and updating the error covariance matrix at the current moment.

[0083] The following further elaborates on the above process involving Kalman filtering in combination with the foregoing specific embodiments and the attached Figure 3 drawings.

[0084] Figure 3 FIG. is a schematic diagram of multi-mode fusion tracking based on a Kalman filter according to an embodiment of the present invention.

[0085] The present invention uses a Kalman filter to estimate the target state, and its process is divided into two stages: prediction and update. In the prediction stage, the state of the previous moment after filtering is predicted using the state transition matrix, as shown in Equation (5): as shown in Equation (5):

[0086] (5),

[0087] where represents the state prediction at the -th moment for the -th moment.

[0088] Meanwhile, the error covariance matrix of the state estimation is updated, as shown in Equation (6):

[0089] (6),

[0090] where is the process noise covariance matrix, represents the prediction of the error covariance matrix at the -th moment for the -th moment, represents the error covariance matrix at the -th moment, represents the transpose matrix of the overall state transition matrix at the -th moment; the error covariance matrix is updated iteratively and continuously, and the initial value of the error covariance matrix can be set according to actual requirements.

[0091] In the update stage, a measurement model is established to associate the state vector with the measurement vector, and its observation equation is shown in Equation (7):

[0092] (7),

[0093] where the measurement matrix takes the corresponding angle and distance parts in the state vector, as shown in Equation (8):

[0094] (8),

[0095] where the measurement matrix the measured values in are obtained by operating on the true values and the noise values. Since there are no first and second derivatives in the measured values, the measurement matrix extracts the first three terms, as shown in Equation (9):

[0096] (9),

[0097] where .

[0098] And represents the measurement noise, and its covariance matrix is . To address the impact of the change in the signal-to-noise ratio of the single-photon radar on the reliability of the measurement data, the present invention introduces an adaptively adjusted observation noise covariance matrix, and its calculation formula is shown in Equation (10):

[0099] (10),

[0100] where is the adjustment coefficient, is the basic observation noise covariance matrix, is the signal-to-noise ratio at the current moment. When the signal-to-noise ratio is high, is small, so that the Kalman gain increases and the measurement data plays a greater role in state update; while when the signal-to-noise ratio is low, increases, and the Kalman gain decreases, weakening the interference of low-reliability data on the filtering result.

[0101] Next, calculate the residual vector (or called the innovation vector, Innovation Vector), as shown in Equation (11):

[0102] (11),

[0103] and the residual covariance (innovation covariance), as shown in Equation (12):

[0104] (12).

[0105] Calculate the Kalman gain using the innovative covariance , as shown in Equation (13):

[0106] (13).

[0107] The state update is as shown in Equation (14):

[0108] (14).

[0109] At the same time, update the error covariance matrix, as shown in Equation (15):

[0110] (15).

[0111] After continuous prediction and update cycles, the above method provided by the present invention finally outputs the target state estimation vector , which contains the current azimuth angle, elevation angle, distance of the target, and various order motion parameters (angular velocity, radial velocity, angular acceleration, radial acceleration). This information can be used for real-time target positioning, trajectory prediction, and tracking control. The whole process is as Figure 3 shown. Starting from data acquisition, through data preprocessing, state modeling, Kalman filter prediction and update, until a stable target state estimation is output. The adaptive observation noise adjustment strategy ensures that the system can maintain high tracking accuracy and stability under different signal-to-noise ratio conditions, thereby giving full play to the respective advantages of single photon radar and infrared imaging, and achieving high-precision and robust tracking of moving targets. In the tracking stage, use the multi-mode fusion lidar provided by the present invention to obtain the azimuth angle and elevation angle of the target; at the same time, combine the single photon detection module to obtain the accurate measurement value of the target distance , so as to achieve real-time high-precision three-dimensional positioning of the target.

[0112] The above multi-modal fusion tracking and positioning method for low-altitude targets provided by the present invention has high-precision target positioning ability: by combining the high-sensitivity ranging ability of the single-photon radar and the large field-of-view detection advantage of infrared imaging, it can achieve high-precision three-dimensional positioning of low-altitude small targets. The above multi-modal fusion tracking and positioning method for low-altitude targets provided by the present invention has stable tracking of maneuvering targets: it uses a high-order motion model to predict the target trajectory and combines multi-source data fusion to ensure stable tracking even when the target is highly maneuvering and the trajectory changes complexly. At the same time, the system uses infrared detection means and has a large field-of-view tracking ability to avoid the target leaving the field of view. The above multi-modal fusion tracking and positioning method for low-altitude targets provided by the present invention has strong tracking anti-interference ability: it dynamically adjusts the data fusion weight according to the signal-to-noise ratio of the single-photon radar, improves the utilization rate of high signal-to-noise ratio data, and reduces the impact of low-quality measurement data on the tracking accuracy.

[0113] Figure 4 It is a schematic structural diagram of a multi-modal fusion tracking and positioning system for low-altitude targets according to an embodiment of the present invention.

[0114] As Figure 4 shown, the above multi-modal fusion tracking and positioning system 400 for low-altitude targets includes a flight data acquisition module 410, a flight data operation module 420, a target state quantity definition module 430, and a three-dimensional tracking and positioning module 440.

[0115] The flight data acquisition module 410 is used to perform infrared tracking and single-photon laser ranging on low-altitude targets using a multi-modal fusion lidar to obtain the angle information, real-time pointing information, and real-time distance information of the low-altitude targets. In one embodiment, the flight data acquisition module 410 can be used to perform the operation S110 described above, which will not be elaborated here.

[0116] The flight data operation module 420 is used to calculate the real-time azimuth angle information and real-time pitch angle information of the low-altitude targets by operating on the angle information and real-time pointing information, and construct a real-time measurement vector of the low-altitude targets using the real-time azimuth angle information, real-time pitch angle information, and real-time distance information. In one embodiment, the flight data operation module 420 can be used to perform the operation S120 described above, which will not be elaborated here.

[0117] The target state quantity definition module 430 is used to define the target state vector of the variable-speed second-order motion model of the low-altitude targets using the real-time measurement vector. In one embodiment, the target state quantity definition module 430 can be used to perform the operation S130 described above, which will not be elaborated here.

[0118] The three-dimensional tracking and positioning module 440 is configured to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector by using a Kalman filter, obtain the target state estimation vector of the low-altitude target, and perform three-dimensional tracking and positioning on the low-altitude target by using the target state estimation vector. In an embodiment, the three-dimensional tracking and positioning module 440 may be configured to execute the operation S140 described above, which will not be elaborated herein.

[0119] According to an embodiment of the present invention, any multiple modules among the flight data acquisition module 410, the flight data operation module 420, the target state quantity definition module 430, and the three-dimensional tracking and positioning module 440 may be combined and implemented in one module, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the flight data acquisition module 410, the flight data operation module 420, the target state quantity definition module 430, and the three-dimensional tracking and positioning module 440 may be at least partially implemented as a hardware circuit, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or any other reasonable manner of integrating or packaging circuits, etc., implemented by hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in any appropriate combination of several of them. Alternatively, at least one of the flight data acquisition module 410, the flight data operation module 420, the target state quantity definition module 430, and the three-dimensional tracking and positioning module 440 may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions may be executed.

[0120] To better illustrate the advantages of the system provided by the present invention, the system provided by the present invention will be verified through experiments and in combination with specific application scenarios below.

[0121] In the monitoring state, the above multi-mode fusion tracking and positioning system for low-altitude targets first uses the passive detection type infrared guidance module to continuously scan the key airspace, obtain the infrared radiation characteristics of the low-altitude target in real time, and achieve all-day and wide-field search and warning. When the infrared imaging identifies a suspected target, the system transmits the target information to the pointing module to guide the detection system to quickly adjust the observation direction to ensure subsequent precise tracking and aiming.

[0122] After target locking, the laser emission module emits invisible laser pulses in the 1550nm band towards the suspected target. The laser in this band has strong atmospheric penetration ability and low detectability, ensuring stable detection performance under complex meteorological conditions. The single-photon detection module synchronously receives the echo signal reflected by the target, and precisely captures the scattered photons of the target through highly sensitive detectors such as single-photon avalanche diodes (SPADs), thereby measuring the flight distance of the target and its weak optical characteristics.

[0123] Subsequently, the system fuses the target angle information (azimuth angle, elevation angle) provided by the passive detection infrared guidance module with the distance information obtained by the single-photon radar to construct complete three-dimensional space measurement data. The fusion algorithm is based on Kalman filtering technology, optimally estimates the measurement information from different data sources, and combines the target motion model to predict its trajectory, achieving high-precision tracking of maneuvering targets.

[0124] During the target tracking process, the system adaptively adjusts the weights of the measurement data, dynamically optimizes the fusion strategy according to the signal-to-noise ratio (SNR) of the single-photon radar, increases the contribution of high-quality measurement data, and at the same time reduces the impact of low SNR data on the tracking accuracy, thereby enhancing the robustness of the system in complex environments. Finally, the system outputs the real-time position information and motion state of the target, providing accurate data support for subsequent threat assessment and defense decision-making.

[0125] Figure 5 It is a block diagram of an electronic device suitable for implementing the multi-mode fusion tracking and positioning method for low-altitude targets according to an embodiment of the present invention.

[0126] As Figure 5 shown, the electronic device 500 according to an embodiment of the present invention includes a processor 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage section 508 into the random access memory (RAM) 503. The processor 501 can include, for example, a general microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application-specific integrated circuit (ASIC)), etc. The processor 501 can also include on-board memory for caching purposes. The processor 501 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0127] In the RAM 503, various programs and data required for the operation of the electronic device 500 are stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. The processor 501 performs various operations of the method flow according to an embodiment of the present invention by executing programs in the ROM 502 and / or the RAM 503. It should be noted that the program can also be stored in one or more memories other than the ROM 502 and the RAM 503. The processor 501 can also perform various operations of the method flow according to an embodiment of the present invention by executing programs stored in the one or more memories.

[0128] According to an embodiment of the present invention, the electronic device 500 may further include an input / output (I / O) interface 505, and the input / output (I / O) interface 505 is also connected to the bus 504. The electronic device 500 may further include one or more of the following components connected to the input / output (I / O) interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed so that a computer program read from it can be installed into the storage portion 508 as needed.

[0129] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist separately without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to an embodiment of the present invention is implemented.

[0130] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the above-described ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503.

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, program segment, or part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0132] Those skilled in the art can understand that the features described in various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in various embodiments of the present invention can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present invention.

[0133] The above describes the embodiments of the present invention. However, these embodiments are only for illustrative purposes and not for limiting the scope of the present invention. Although the embodiments are described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. Without departing from the scope of the present invention, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present invention.

Claims

1. A multi-mode fusion tracking and positioning method for low-altitude targets, characterized in that: The method comprises: A multi-mode fusion laser radar is used to perform infrared tracking and single-photon laser ranging on low-altitude targets to obtain angle information, real-time pointing information, and real-time distance information of the low-altitude targets. The multi-mode fusion laser radar includes a passive detection infrared guidance module, a single-photon laser emission module, a single-photon laser detection module, a pointing module, and an electronics module. Calculating the angle information and the real-time pointing information to obtain real-time azimuth information and real-time pitch angle information of the low-altitude target, and constructing a real-time measurement vector of the low-altitude target using the real-time azimuth information, the real-time pitch angle information, and the real-time distance information; Defining a target state vector of a variable speed second-order motion model of the low-altitude target using the real-time measurement vector; Using a Kalman filter to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector to obtain a target state estimation vector of the low-altitude target, and using the target state estimation vector to perform three-dimensional tracking and positioning of the low-altitude target; Among them, the low-altitude target multi-mode fusion radar is used to perform infrared tracking and single-photon laser ranging on the low-altitude target, and the angle information, real-time pointing information and real-time distance information of the low-altitude target are obtained, including: Using the passive detection infrared guidance module to perform infrared tracking on the low-altitude target to obtain an infrared image of the low-altitude target, and performing image processing on the infrared image to obtain angle information of the low-altitude target, wherein the angle information includes an azimuth miss amount and a pitch miss amount; The pointing module is used to obtain real-time pointing information of the low-altitude target, and the single-photon laser emission module and the single-photon laser detection module are used to collect real-time distance information and real-time signal-to-noise ratio information of the low-altitude target; The step of calculating the angle information and the real-time pointing information to obtain the real-time azimuth angle information and the real-time pitch angle information of the low-altitude target includes: The azimuth in the real-time pointing information and the azimuth miss amount are calculated to obtain the real-time azimuth information, and the pitch angle in the real-time pointing information and the pitch miss amount are calculated to obtain the real-time pitch angle information.

2. The method according to claim 1, characterized in that Defining the target state vector of the variable speed second-order motion model of the low-altitude target using the real-time measurement vector includes: Calculating a first-order steering quantity and a second-order steering quantity of the real-time measurement vector, and constructing the target state vector using the real-time measurement vector, the first-order steering quantity of the real-time measurement vector, and the second-order steering quantity of the real-time measurement vector; Calculating the state transfer matrix of the real-time measurement vector, the first-order steering quantity of the real-time measurement vector, and the second-order steering quantity of the real-time measurement vector respectively by using the variable speed second-order motion model of the low-altitude target; The state transfer matrix of the real-time measurement vector, the state transfer matrix of the first-order pilot quantity of the real-time measurement vector and the state transfer matrix of the second-order pilot quantity of the real-time measurement vector are formed into an overall state transfer matrix of the low-altitude target in the form of a block diagonal matrix.

3. The method according to claim 2, characterized in that Using a Kalman filter to alternately and iteratively perform state prediction processing and state update processing on the target state vector and the real-time measurement vector to obtain a target state estimation vector of the low-altitude target includes: Constructing a target state estimation vector at a current moment by using the overall state transfer matrix of the low-altitude target and the target state estimation vector filtered by the Kalman filter at a previous moment; The overall state transfer matrix of the low-altitude target, the process noise covariance matrix and the error covariance matrix of the previous moment are used to construct the error covariance matrix of the current moment and thus complete the state prediction processing of the Kalman filter, wherein the error covariance matrix is used for state update estimation.

4. The method according to claim 3, characterized in that Also includes: Obtaining an adaptively adjustable observation noise covariance matrix at the current moment using the real-time signal-to-noise ratio information at the current moment, a basic observation noise covariance matrix, and a preset adjustment coefficient, and obtaining the observation noise at the current moment based on the observation noise covariance matrix at the current moment; The measurement model at the current moment is constructed using the observation noise, measurement matrix and target state estimation vector at the current moment, and the state update processing is performed on the target state estimation vector at the current moment using the measurement model at the current moment.

5. The method according to claim 4, characterized in that Performing state update processing on the target state estimation vector at the current moment by using the measurement model at the current moment includes: Calculating the measurement model at the current moment and the target state estimation vector to obtain the residual vector at the current moment; Calculating the error covariance matrix, the measurement matrix, and the observation noise covariance matrix at the current moment to obtain the residual covariance at the current moment; Calculating the Kalman gain at the current moment using the error covariance matrix, the measurement matrix, and the residual covariance at the current moment; The target state estimation vector at the current moment is updated using the Kalman gain and the residual vector at the current moment, and the error covariance matrix at the current moment is updated.

6. A multi-mode fusion tracking and positioning system for low-altitude targets, characterized in that: The system comprises: A flight data acquisition module is used to perform infrared tracking and single-photon laser ranging on low-altitude targets using a multi-mode fusion laser radar to obtain angle information, real-time pointing information, and real-time distance information of the low-altitude targets. The multi-mode fusion laser radar includes a passive detection infrared guidance module, a single-photon laser emission module, a single-photon laser detection module, a pointing module, and an electronics module. a flight data calculation module, configured to calculate the angle information and the real-time pointing information to obtain real-time azimuth information and real-time pitch angle information of the low-altitude target, and construct a real-time measurement vector of the low-altitude target using the real-time azimuth information, the real-time pitch angle information, and the real-time distance information; a target state quantity definition module, configured to define a target state vector of a variable speed second-order motion model of the low-altitude target using the real-time measurement vector; a three-dimensional tracking and positioning module, configured to perform state prediction processing and state update processing on the target state vector and the real-time measurement vector alternately and iteratively using a Kalman filter to obtain a target state estimation vector of the low-altitude target, and perform three-dimensional tracking and positioning of the low-altitude target using the target state estimation vector; Among them, the low-altitude target multi-mode fusion radar is used to perform infrared tracking and single-photon laser ranging on the low-altitude target, and the angle information, real-time pointing information and real-time distance information of the low-altitude target are obtained, including: Using the passive detection infrared guidance module to perform infrared tracking on the low-altitude target to obtain an infrared image of the low-altitude target, and performing image processing on the infrared image to obtain angle information of the low-altitude target, wherein the angle information includes an azimuth miss amount and a pitch miss amount; The pointing module is used to obtain real-time pointing information of the low-altitude target, and the single-photon laser emission module and the single-photon laser detection module are used to collect real-time distance information and real-time signal-to-noise ratio information of the low-altitude target; The step of calculating the angle information and the real-time pointing information to obtain the real-time azimuth angle information and the real-time pitch angle information of the low-altitude target includes: The azimuth in the real-time pointing information and the azimuth miss amount are calculated to obtain the real-time azimuth information, and the pitch angle in the real-time pointing information and the pitch miss amount are calculated to obtain the real-time pitch angle information.

7. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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