Tracking maintaining method of movable platform warning radar under pitching dimension large error

Abstract

The invention discloses a tracking maintaining method of a moving platform warning radar under a large pitch dimension error. The tracking maintaining method comprises the following steps: carrying out attenuation compression on a pitch angle to obtain a compressed pitch angle; converting the compressed pitch angle and other measurement information to an earth-centered earth-fixed coordinate system to obtain a first offset, and obtaining a measured earth-centered earth-fixed value according to the first offset; obtaining a filtering result at the t-th moment according to the measured earth-centered earth-consolidation value at the t-th moment and the predicted position at the t-th moment; based on an inversion mode, a pitch angle of compression filtering is obtained according to a filtering result; sequentially carrying out amplification reduction and threshold judgment on the compressed and filtered pitch angle to obtain a pitch angle to be output; and obtaining a final earth-centered earth-fixed output value according to the pitch angle to be output and other filtering information. The tracking maintaining method is a compression processing method based on the pitching dimension, can keep continuous tracking of the target in the direction, and has certain pitching dimension tracking precision.

Description

Technical Field

[0001] This invention belongs to the field of early warning radar technology, specifically relating to a method for maintaining tracking of a moving platform early warning radar under large elevation errors. Background Technology

[0002] Radar target tracking tasks mainly involve data association and tracking filtering. The former refers to pairing radar measurement data at a certain moment with measurement data or tracks at other moments, while the latter refers to accurately estimating the current target's motion state based on current and previous radar measurements. Data association relies on prior information such as the target motion model, filter covariance, and gate threshold. The quality of the tracking filtering algorithm depends on factors such as the statistical characteristics of process and measurement noise, and initial state conditions. If the measurement deviates significantly from the actual situation, it will lead to divergent state estimation and completely incorrect tracking.

[0003] Excessive pitch dimension error due to hardware limitations is typically addressed by discarding this dimension for dimensionality reduction. However, this approach is usually applied to radars with a fixed observation position. Moving platform early warning radars, because they are in motion and their observation position changes constantly, usually map the positions of the early warning radar and the target to a unified coordinate system (such as the geocentric ECEF coordinate system). This transformation is a three-dimensional mapping, requiring the range, azimuth, and pitch dimensions to be converted to a Cartesian coordinate system simultaneously; therefore, the pitch dimension cannot be directly discarded.

[0004] Existing dimensionality reduction techniques that discard dimensions are only applicable to radars with a fixed observation position. For moving platforms like early warning radars, the range, azimuth, and elevation information they observe is based on the current state of the radar platform (for example, if a target is observed at 0° azimuth on the early warning radar, but the radar platform's azimuth changes by 90°, the azimuth of the target observed by the early warning radar will track the 90° change, and the data from the two observations will not be in the same coordinate system). Therefore, this dimensionality reduction method cannot be used on moving platform radars. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a method for maintaining tracking of a moving platform early warning radar under large pitch error.

[0006] The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a method for maintaining tracking under large elevation errors in a moving platform early warning radar, comprising: Step 1: Obtain the pitch angle from radar signal processing, and attenuate and compress the pitch angle to obtain the compressed pitch angle; Step 2: Convert the compressed pitch angle and other measurement information from polar coordinates to the platform rectangular coordinate system to obtain the measured rectangular coordinate value. Based on the measured rectangular coordinate value, obtain the first offset relative to the platform in the geocentric coordinate system. Based on the first offset, obtain the measured geocentric value. Step 3: In the Kalman filter, based on the associated first... t The measured value of the Earth's core at time and the first t The predicted position at time 1 is obtained t The filtering result at time; Step 4: Based on the inversion method, obtain the pitch angle of the compressed filter according to the filtering result; Step 5: Sequentially amplify and restore the pitch angle of the compressed filter and perform threshold judgment to obtain the pitch angle to be output; Step 6: Obtain the final Earth-center solid-state output value based on the pitch angle to be output and other filtering information.

[0007] In one embodiment of the present invention, step 1 includes: Step 1.1: Obtain the elevation angle from radar signal processing; Step 1.2: Attenuate and compress the pitch angle using a fixed attenuation value to obtain the compressed pitch angle, wherein the fixed attenuation value is one-third of the pitch angle beamwidth. In one embodiment of the present invention, step 2 includes: Step 2.1: Convert the compressed pitch angle and other measurement information from polar coordinates to the platform's rectangular coordinate system to obtain the measured rectangular coordinate values, which are expressed as follows:

[0008] in, The measured rectangular coordinate values, ( , , ( ) represents the three coordinate components of the target in the platform's Cartesian coordinate system. The straight-line distance between the target and the radar. It is the azimuth angle. This is the compressed pitch angle; Step 2.2: Based on the measured rectangular coordinate values, the rotation matrix for transforming the platform's rectangular coordinate system to the northeast-sky coordinate system, and the rotation matrix for transforming the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system, the first offset is obtained. The first offset is expressed as:

[0009] in, This is the first offset. This is the rotation matrix for transforming the platform from the Cartesian coordinate system to the Northeast-Eastern-Sky coordinate system. This is the rotation matrix for transforming the coordinate system from the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system; Step 2.3: Obtain the geocentric coordinates of the platform based on the radius of curvature, and obtain the measured geocentric value based on the geocentric coordinates of the platform and the first offset. In one embodiment of the present invention, step 2.3 includes: Step 2.31: Obtain the radius of curvature, which is expressed as:

[0010] in, Let be the radius of curvature. For the Earth's semi-major axis, The square of the eccentricity. For dimensions; Step 2.32: Obtain the geocentric coordinates of the platform based on the radius of curvature, the latitude, longitude, and altitude. The geocentric coordinates of the platform are expressed as:

[0011] in, For the platform's geocentric coordinates, ( , , ) represents the three coordinate components of the platform's geocentric coordinate system. Longitude For height; Step 2.33: Obtain the measured geocentric coordinates based on the first offset and the geocentric coordinates of the platform. The measured geocentric coordinates are expressed as follows:

[0012] in, This refers to the measured value of the Earth's core solidity. In one embodiment of the present invention, step 3 includes: Step 3.1: In the Kalman filter, for the first... t The filtered result at time -1 is used for Kalman prediction to obtain the predicted position at time t. Step 3.2: Using the predicted position at time t as the center and a preset spherical gate with a preset value as the radius, perform nearest neighbor association. If the measured geocentric solid value at time t is located in the preset spherical gate, then perform the association operation. Step 3.3, according to the aforementioned... t The measured geocentric solid value at time and the first tThe predicted position at time t is updated using Kalman filtering to obtain the t-th time. t The filtering result at time 1. In one embodiment of the present invention, step 4 includes: Step 4.1: Based on the filtering result and the geocentric coordinates of the platform, obtain the second offset of the filtering result relative to the platform in the ECEF coordinate system. The second offset is expressed as:

[0013] in, This is the second offset. The result of the filtering is as follows. The coordinates of the platform's geocentric coordinates; Step 4.2: Obtain the Cartesian coordinates relative to the platform based on the second offset; Step 4.3: Obtain the pitch angle for compression filtering based on the Cartesian coordinates relative to the platform. In one embodiment of the present invention, step 4.2 includes: Step 4.21: Invert the rotation matrix that transforms the platform rectangular coordinate system to the northeast-sky coordinate system to obtain the first inverse rotation matrix; invert the rotation matrix that transforms the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system to obtain the second inverse rotation matrix. Step 4.22: Obtain the Cartesian coordinates relative to the platform based on the first inverse rotation matrix, the second inverse rotation matrix, and the second offset. The Cartesian coordinates relative to the platform are expressed as follows:

[0014] in, These are the rectangular coordinates relative to the platform. This is the first inverse rotation matrix. This is the second inverse rotation matrix. In one embodiment of the present invention, step 4.3 includes: Step 4.31: Convert the rectangular coordinates relative to the platform to polar coordinates to obtain polar coordinates, which are expressed as follows:

[0015] in, These are polar coordinate values. , , These are the three coordinate components of the rectangular coordinates relative to the platform; Step 4.32: Obtain the pitch angle of the compressed filter based on the polar coordinates. The pitch angle of the compressed filter is expressed as:

[0016] in, The pitch angle is for compression filtering. In one embodiment of the present invention, step 5 includes: Step 5.1: Use the fixed attenuation value to amplify and restore the pitch angle of the compressed filter to obtain the restored pitch angle; Step 5.2: Determine whether the restored pitch angle exceeds the pitch angle range. If yes, use the range-azimuth pitch angle obtained in Step 1 as the pitch angle to be output. If no, use the restored pitch angle as the pitch angle to be output. In one embodiment of the present invention, step 5 includes: Step 5.1: Use the fixed attenuation value to amplify and restore the pitch angle of the compressed filter to obtain the restored pitch angle; Step 5.2: Determine whether the restored pitch angle exceeds the pitch angle range. If yes, use the range-azimuth pitch angle obtained in Step 1 as the pitch angle to be output. If no, use the restored pitch angle as the pitch angle to be output. In one embodiment of the present invention, step 6 includes: Step 6.1: Convert the pitch angle and other filtering information to be output from polar coordinates to the platform rectangular coordinate system, then from the platform rectangular coordinate system to the northeast-sky coordinate system, and then from the northeast-sky coordinate system to the geocentric-ground-fixed coordinate system to obtain the third offset. Step 6.2: Obtain the final geocentric solid output value based on the third offset.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a sustained tracking method for a moving platform early warning radar under large elevation dimension errors. When the early warning radar uses a fixed elevation dimension wide beam for elevation search, this sustained tracking method can directly compress the elevation angle obtained from the measurement information, quickly and easily filter and predict the data to obtain a filter that can stably track and correlate it. Finally, the output of the filter is used to restore the elevation, and the final ground-centric output value is calculated and sent to the display and control system. The sustained tracking method provided by this invention is based on an elevation dimension compression processing method, which can retain continuous tracking of the target in azimuth and has a certain elevation dimension tracking accuracy.

[0018] The tracking method provided by this invention can be directly applied to the engineering implementation of motion platforms.

[0019] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for maintaining tracking under large pitch error in a dynamic platform early warning radar, as provided in an embodiment of the present invention. Figure 2 This is a polar coordinate and platform rectangular coordinate diagram provided in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the relationship between the Northeast Altitude (ENU) coordinate system and the platform Cartesian coordinate system (FLU) provided in an embodiment of the present invention; Figure 4 This is a top-view diagram of yaw angle rotation provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of a head-up view with rotation of the tilt angle provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a forward roll angle rotation provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the distance difference between uncompressed filtered prediction and measurement data provided in an embodiment of the present invention; Figure 8 This is a distance difference between compressed filtered prediction and measurement data provided in an embodiment of the present invention; Figure 9 This is a display diagram of the true azimuth angle and the tracking estimate provided in an embodiment of the present invention; Figure 10 This is a comparison diagram of a pitch angle provided in an embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0022] Example 1 When mobile platform early warning radar conducts airspace observation, it typically scans the airspace for range, azimuth, and elevation. Due to cost considerations and radar reconnaissance and positioning, some radars measure range and azimuth more precisely, while using a fixed wide beam in the elevation dimension. This results in excessively large angular measurement errors in the elevation dimension. When performing long-range scans, the small azimuth error combined with the large elevation error leads to significant discrepancies between the measured target position and its actual location. Tracking filtering relies on the correction of measurement information; under these circumstances, using filtering algorithms for predictive correlation will fail due to the large measurement errors, causing the filter to fail to converge, gradually diverge, and ultimately lose target tracking.

[0023] To address the above problems, this invention provides a method for maintaining tracking under large pitch error conditions using a moving platform early warning radar. Please refer to [link to relevant documentation]. Figure 1 , Figure 1This is a flowchart illustrating a method for maintaining tracking under large pitch dimension errors in a moving platform early warning radar, as provided in an embodiment of the present invention. The method includes: Step 1: Obtain the elevation angle from radar signal processing, and attenuate and compress the elevation angle to obtain the compressed elevation angle.

[0024] Step 1.1: Obtain the elevation angle from radar signal processing.

[0025] Specifically, the radar in this embodiment is a warning radar. The received data for radar signal processing is the signal returned by the electromagnetic wave sent by the radar signal source. Then, information such as range, azimuth, and elevation angle are obtained through analysis.

[0026] Step 1.2: Attenuate and compress the pitch angle using a fixed attenuation value to obtain the compressed pitch angle, where the fixed attenuation value is one-third of the pitch angle beamwidth.

[0027] Specifically, the fixed elevation beamwidth of the radar is first multiplied by one-third to obtain a fixed attenuation value. Then, the elevation angle is divided by the fixed attenuation value to achieve attenuation compression, ultimately yielding the compressed elevation angle. For example, when the range-azimuth elevation angle is -90° to 90° and the elevation beamwidth is 30°, the fixed attenuation value is 10, and the compressed elevation angle is -9° to 9°.

[0028] Step 2: Convert the compressed pitch angle and other measurement information (such as distance and azimuth) from polar coordinates to the platform rectangular coordinate system to obtain the measured rectangular coordinate values. Based on the measured rectangular coordinate values, obtain the first offset relative to the platform in the geocentric coordinate system. Based on the first offset, obtain the measured geocentric value.

[0029] Step 2.1, as follows Figure 2 As shown, the compressed pitch angle and other measurement information are converted from polar coordinates to the platform's rectangular coordinate system to obtain the measured rectangular coordinate values.

[0030] Here, the measured rectangular coordinate values ​​are expressed as:

[0031] in, The measured rectangular coordinate values, ( , , ( ) represents the three coordinate components of the target in the platform's Cartesian coordinate system. The straight-line distance between the target and the radar. It is the azimuth angle. This is the compressed pitch angle.

[0032] Step 2.2: Obtain the first offset based on the measured rectangular coordinate values, the rotation matrix for transforming the platform's rectangular coordinate system to the northeast-sky coordinate system, and the rotation matrix for transforming the northeast-sky coordinate system to the geocentric coordinate system.

[0033] Specifically, such as Figure 3 As shown, converting the platform's Cartesian coordinates to the Northeast-Sky coordinate system requires the platform's yaw, pitch, and roll attitude information.

[0034] like Figure 4 As shown, from above... z Rotation of the axis, towards y Rotation along the axis (or to the left) is positive (or rotation from east to north is positive). [0°, 360°] or [0°, 180°][-180°, 0], that is:

[0035] in, This is the yaw angle.

[0036] like Figure 5 As shown, looking around at eye level Rotate downwards to make it positive. [-90°, 90°], that is:

[0037] in, It is the pitch angle. like Figure 6 As shown, forward view around Rotation of the axis, rolling to the left is positive. [-90°, 90°], that is:

[0038] in, This refers to the roll angle. Multiplying the matrices corresponding to the three attitude angles yields the rotation matrix for transforming the platform from Cartesian coordinates to Northeast-East-South coordinates. The rotation matrix for transforming the platform from Cartesian coordinates to Northeast-Eastern-Heaven coordinates is expressed as:

[0039] in, This is the rotation matrix for transforming the platform from the Cartesian coordinate system to the Northeast-Eastern-Sky coordinate system. To bypass x Axis rotation matrix, To bypass y Axis rotation matrix, To bypass z The rotation matrix of the axis. The rotation matrix for transforming from the Northeast-Sky coordinate system to the Geocentric-Earth-Fixed coordinate system can be calculated based on the platform's longitude and latitude. The rotation matrix for transforming from the Northeast-Sky coordinate system to the Geocentric-Earth-Fixed coordinate system is expressed as follows:

[0040] in, This is the rotation matrix for transforming from the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system. Longitude is the arc measured eastward from the Prime Meridian to the target point. [0°, 360°], Latitude is the angle between the normal to the Earth's ellipsoid and the equatorial plane. [-90°, 90°].

[0041] Finally, multiplying the measured rectangular coordinate values ​​by the two rotation matrices yields the first offset of the measurement relative to the platform in the geocentric coordinate system. The first offset is expressed as:

[0042] in, This is the first offset.

[0043] Step 2.3: Obtain the geocentric coordinates of the platform based on the radius of curvature, and obtain the measured geocentric value based on the geocentric coordinates and the first offset.

[0044] Step 2.31: Obtain the radius of curvature, which is expressed as:

[0045] in, Let be the radius of curvature. The semi-major axis of the Earth is approximately 6,378,137 meters. The square of the eccentricity is approximately 0.00669437999014.

[0046] Step 2.32: Obtain the geocentric and geofixed coordinates of the platform based on the radius of curvature, latitude, longitude, and altitude. The geocentric and geofixed coordinates of the platform are expressed as:

[0047] in, For the platform's geocentric coordinates, ( , , ) represents the three coordinate components of the platform's geocentric coordinate system. The height is the ellipsoidal height, expressed in meters.

[0048] Step 2.33: Obtain the measured geocentric coordinates based on the first offset and the geocentric coordinates of the platform.

[0049] Specifically, the geocentric coordinate system of the platform is calculated by using the platform's longitude, latitude, and altitude. Then, the measured geocentric value is obtained by adding the platform value to the first offset relative to the measurement.

[0050] Here, the measured Earth-core solid value is expressed as:

[0051] in, This refers to the measured value of the Earth's core solidity.

[0052] Step 3: In the Kalman filter, based on the associated first... t The measured value of the Earth's core at time and the first t The predicted position at time 1 is obtained t The filtering result at time 1.

[0053] Step 3.1: In the Kalman filter, for the first... t The filtered result at time -1 is used for Kalman prediction to obtain the predicted position at time t.

[0054] Specifically, in a Kalman filter, a first spherical gate is set with the measured geocentric value received at the first moment as the center and a first fixed value as the radius. At the second moment, the Kalman filter receives another measured geocentric value. If this measured geocentric value is within the first spherical gate, then the measured geocentric values ​​at the two moments are correlated, meaning they are considered to originate from the same target. Therefore, the Kalman filter obtains a velocity based on the correlated measured geocentric values ​​at the two moments. The Kalman filter can then make predictions based on the filtering results of the previous moment, i.e., by analyzing the data from the previous moment... t The filtered result at time -1 is used for Kalman prediction to obtain the predicted position at time t.

[0055] Step 3.2: Using the predicted position at time t as the center and the preset value as the radius, set a preset spherical gate and perform nearest neighbor association. If the measured geocentric solid value at time t is located in the preset spherical gate, then perform the association operation.

[0056] Specifically, with the first t The predicted position at time t is the center of a circle, and a preset spherical gate (also the second fixed value, which is smaller than the first fixed value) is set with a radius of 0. If the Kalman filter... t If the measured values ​​of the Earth's core and solid surface that are received at any given time are within a preset spherical gate, it indicates that they belong to the same target, and thus they are correlated.

[0057] In this embodiment, the size of the spherical gate is positively correlated with the radar's effective range. The simulation below uses a maximum effective range of 300km and a spherical gate size of 5km for nearest neighbor association. To reduce the number of non-target points involved in multi-target scene association, additional comparisons are made between the converted azimuth angle (whether the difference is less than 0.5°) and radial distance (whether the difference is less than 1km) of the measured and predicted values.

[0058] Step 3.3, according to the first t The measured value of the Earth's core at time and the first t The predicted position at time t is updated using Kalman filtering to obtain the t-th time. t The filtering result at time 1.

[0059] Specifically, in the Kalman filter, the first... t The measured value of the Earth's core at time and the first t The predicted position at time step is updated using Kalman filtering, which involves a weighted summation operation to obtain the result. t The filtering result at time step [time] is then retained in the Kalman filter to maintain the internal filtering prediction correlation for the next iteration.

[0060] Figure 7 It is the distance difference between the uncompressed filtered prediction and the measured data. Figure 8 This represents the distance difference between the compressed filtered prediction value and the measured data. During the filtering process, the filtered prediction value is first calculated, and then a gate is set centered on this prediction value. Points falling within the gate are selected as the association targets. It can be seen that the distance difference between the uncompressed filtered prediction value and the measured data repeatedly exceeds 10km, even reaching 20km. Forcing an association would require opening a huge gate. While this might achieve association at that point, the large fluctuations would cause the filter to lose convergence, gradually diverge, and ultimately become completely erroneous. However, the difference between the compressed filtered prediction value and the measured data stabilizes within 3km.

[0061] Step 4: Based on the inversion method, obtain the pitch angle of the compressed filter according to the filtering result.

[0062] Step 4.1: Based on the filtering result and the platform's geocentric and geofixed coordinates, obtain the second offset of the filtering result relative to the platform in the ECEF coordinate system. The second offset is expressed as:

[0063] in, This is the second offset. The result of the filtering is as follows. The coordinates are the geocentric coordinates of the platform.

[0064] Step 4.2: Obtain the rectangular coordinates relative to the platform based on the second offset.

[0065] Step 4.21: Invert the rotation matrix that transforms the platform rectangular coordinate system to the northeast-sky coordinate system to obtain the first inverse rotation matrix; invert the rotation matrix that transforms the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system to obtain the second inverse rotation matrix. Step 4.22: Obtain the Cartesian coordinates relative to the platform based on the first inverse rotation matrix, the second inverse rotation matrix, and the second offset. The Cartesian coordinates relative to the platform are expressed as follows:

[0066]

[0067]

[0068] in, These are the rectangular coordinates relative to the platform. This is the first inverse rotation matrix. This is the second inverse rotation matrix. Step 4.3: Obtain the pitch angle for compression filtering based on the rectangular coordinates relative to the platform.

[0069] Step 4.31: Transform the rectangular coordinates relative to the platform to the polar coordinate system to obtain the polar coordinate values, which are expressed as follows:

[0070] in, These are polar coordinate values. , , These are the three coordinate components of the rectangular coordinates relative to the platform; Step 4.32: Obtain the pitch angle for the compressed filter based on the polar coordinates. The pitch angle for the compressed filter is expressed as:

[0071]

[0072] in, The pitch angle for compression filtering. The azimuth angle is for compression filtering. Step 5: Perform amplification and restoration processing and threshold judgment on the pitch angle of the compressed filter in sequence to obtain the pitch angle to be output.

[0073] Step 5.1: Use a fixed attenuation value to amplify and restore the pitch angle of the compressed filter to obtain the restored pitch angle.

[0074] Specifically, the fixed attenuation value from step 1 is multiplied by the pitch angle of the compressed filter to obtain the restored pitch angle.

[0075] Step 5.2: Determine whether the restored pitch angle exceeds the pitch angle range. If yes, use the range-azimuth pitch angle obtained in Step 1 as the output pitch angle. If no, use the restored pitch angle as the output pitch angle. The pitch angle range is -90° to 90°.

[0076] Step 6: Obtain the final geocentric output value based on the pitch angle to be output and other filtering information (such as filtered distance and azimuth).

[0077] Step 6.1: Convert the pitch angle and other filtering information to be output from polar coordinates to the platform rectangular coordinate system, then from the platform rectangular coordinate system to the northeast-sky coordinate system, and then from the northeast-sky coordinate system to the geocentric-ground-fixed coordinate system to obtain the third offset.

[0078] Specifically, following the conversion methods in steps 2.1 and 2.2, the pitch angle to be output is sequentially converted from polar coordinates to the platform rectangular coordinate system, the northeast-sky coordinate system, and the geocentric-ground-fixed coordinate system, thereby obtaining the third offset relative to the platform.

[0079] Step 6.2: Obtain the final Earth Core Solid Output Value based on the third offset.

[0080] Specifically, following the operation method in step 2.3, the final geocentric output value is obtained based on the geocentric coordinates of the third offset platform, and the final geocentric output value is sent to the display control for display.

[0081] The simulation scenario is set as follows: Platform initial coordinates ( x The initial coordinates of the target (y, z) are [0m, 0m, 0m], and the target's initial coordinates are [200000m, 200000m, 0]. The target moves in a V-shape. x The aircraft flies at a speed of 300 m / s towards the early warning radar. The pitch angle is fixed, and the beamwidth is set to 30° (the pitch angle value is fixed, and the attenuation is compressed to one-third of the wide pitch beamwidth, i.e., 10). A 9-dimensional uniformly accelerated motion model is used for Kalman filtering. Because of the measurement error angle in the pitch dimension, and considering the significant impact of projection onto the platform's Cartesian coordinate system on the Z-axis, the noise standard deviation of the Z-axis is set to 5 times that of the X and Y axes. The pitch angle (unit: °) is set to a normal distribution of N(0, 1.5²), the azimuth angle (unit: °) is set to a normal distribution of N(0, 0.3²), and the radial distance (unit: m) is set to a normal distribution of N(0, 50²).

[0082] pass Figure 9 and Figure 10As can be seen, after pitch dimension compression and then tracking, the azimuth angle can maintain a continuous and stable tracking, and there is also a certain tracking accuracy in the pitch dimension.

[0083] This invention provides a sustained tracking method for a moving platform early warning radar under large elevation dimension errors. This sustained tracking method can be directly applied to the engineering implementation of moving platforms. When the early warning radar uses a fixed elevation dimension wide beam for elevation search, it can directly compress the elevation angle obtained from the measurement information and quickly send it to the data processing modules such as filtering, prediction, correlation, and output to rapidly obtain a filter that can stably track and correlate. Finally, the output of this filter is used to restore the elevation and calculate the true ECEF coordinates, which are then sent to the display and control system. The sustained tracking method provided by this invention is based on an elevation dimension compression processing method, which can retain continuous tracking of the target in azimuth and has a certain elevation dimension tracking accuracy.

[0084] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0085] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0086] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings and the disclosure in carrying out the claimed invention. In this specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. While certain measures are described in different embodiments, this does not mean that these measures cannot be combined to produce good results.

[0087] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for maintaining tracking under large elevation errors in a moving platform early warning radar, characterized in that, include: Step 1: Obtain the pitch angle from radar signal processing, and attenuate and compress the pitch angle to obtain the compressed pitch angle; Step 2: Convert the compressed pitch angle and other measurement information from polar coordinates to the platform rectangular coordinate system to obtain the measured rectangular coordinate value. Based on the measured rectangular coordinate value, obtain the first offset relative to the platform in the geocentric coordinate system. Based on the first offset, obtain the measured geocentric value. Step 3: In the Kalman filter, based on the associated first... t The measured value of the Earth's core at time and the first t The predicted position at time 1 is obtained t The filtering result at time; Step 4: Based on the inversion method, obtain the pitch angle of the compressed filter according to the filtering result; Step 5: Sequentially amplify and restore the pitch angle of the compressed filter and perform threshold judgment to obtain the pitch angle to be output; Step 6: Obtain the final Earth-center solid-state output value based on the pitch angle to be output and other filtering information.

2. The tracking maintenance method according to claim 1, characterized in that, Step 1 includes: Step 1.1: Obtain the elevation angle from radar signal processing; Step 1.2: Attenuate and compress the pitch angle using a fixed attenuation value to obtain the compressed pitch angle, wherein the fixed attenuation value is one-third of the pitch angle beamwidth.

3. The tracking maintenance method according to claim 1, characterized in that, Step 2 includes: Step 2.1: Convert the compressed pitch angle and other measurement information from polar coordinates to the platform's rectangular coordinate system to obtain the measured rectangular coordinate values, which are expressed as follows: in, The measured rectangular coordinate values, ( , , ( ) represents the three coordinate components of the target in the platform's Cartesian coordinate system. The straight-line distance between the target and the radar. It is the azimuth angle. This is the compressed pitch angle; Step 2.2: Based on the measured rectangular coordinate values, the rotation matrix for transforming the platform's rectangular coordinate system to the northeast-sky coordinate system, and the rotation matrix for transforming the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system, the first offset is obtained. The first offset is expressed as: in, This is the first offset. This is the rotation matrix for transforming the platform from the Cartesian coordinate system to the Northeast-Eastern-Sky coordinate system. This is the rotation matrix for transforming the coordinate system from the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system; Step 2.3: Obtain the geocentric coordinates of the platform based on the radius of curvature, and obtain the measured geocentric value based on the geocentric coordinates of the platform and the first offset.

4. The tracking maintenance method according to claim 1, characterized in that, Step 2.3 includes: Step 2.31: Obtain the radius of curvature, which is expressed as: in, Let be the radius of curvature. For the Earth's semi-major axis, The square of the eccentricity. For dimensions; Step 2.32: Obtain the geocentric coordinates of the platform based on the radius of curvature, the latitude, longitude, and altitude. The geocentric coordinates of the platform are expressed as: in, For the platform's geocentric coordinates, ( , , ) represents the three coordinate components of the platform's geocentric coordinate system. Longitude For height; Step 2.33: Obtain the measured geocentric coordinates based on the first offset and the geocentric coordinates of the platform. The measured geocentric coordinates are expressed as follows: in, This refers to the measured value of the Earth's core solidity.

5. The tracking maintenance method according to claim 1, characterized in that, Step 3 includes: Step 3.1: In the Kalman filter, for the first... t The filtered result at time -1 is used for Kalman prediction to obtain the predicted position at time t. Step 3.2: Using the predicted position at time t as the center and a preset spherical gate with a preset value as the radius, perform nearest neighbor association. If the measured geocentric solid value at time t is located in the preset spherical gate, then perform the association operation. Step 3.3, according to the aforementioned... t The measured geocentric solid value at time and the first t The predicted position at time t is updated using Kalman filtering to obtain the t-th time. t The filtering result at time 1.

6. The tracking maintenance method according to claim 1, characterized in that, Step 4 includes: Step 4.1: Based on the filtering result and the geocentric coordinates of the platform, obtain the second offset of the filtering result relative to the platform in the ECEF coordinate system. The second offset is expressed as: in, This is the second offset. The result of the filtering is as follows. The coordinates of the platform's geocentric coordinates; Step 4.2: Obtain the Cartesian coordinates relative to the platform based on the second offset; Step 4.3: Obtain the pitch angle for compression filtering based on the Cartesian coordinates relative to the platform.

7. The tracking maintenance method according to claim 6, characterized in that, Step 4.2 includes: Step 4.21: Invert the rotation matrix that transforms the platform rectangular coordinate system to the northeast-sky coordinate system to obtain the first inverse rotation matrix; invert the rotation matrix that transforms the northeast-sky coordinate system to the geocentric-earth-fixed coordinate system to obtain the second inverse rotation matrix. Step 4.22: Obtain the Cartesian coordinates relative to the platform based on the first inverse rotation matrix, the second inverse rotation matrix, and the second offset. The Cartesian coordinates relative to the platform are expressed as follows: in, These are the rectangular coordinates relative to the platform. This is the first inverse rotation matrix. This is the second inverse rotation matrix.

8. The tracking maintenance method according to claim 6, characterized in that, Step 4.3 includes: Step 4.31: Convert the rectangular coordinates relative to the platform to polar coordinates to obtain polar coordinates, which are expressed as follows: in, These are polar coordinate values. , , These are the three coordinate components of the rectangular coordinates relative to the platform; Step 4.32: Obtain the pitch angle of the compressed filter based on the polar coordinates. The pitch angle of the compressed filter is expressed as: in, The pitch angle is for compression filtering.

9. The tracking maintenance method according to claim 2, characterized in that, Step 5 includes: Step 5.1: Use the fixed attenuation value to amplify and restore the pitch angle of the compressed filter to obtain the restored pitch angle; Step 5.2: Determine whether the restored pitch angle exceeds the pitch angle range. If yes, use the range-azimuth pitch angle obtained in Step 1 as the pitch angle to be output. If no, use the restored pitch angle as the pitch angle to be output.

10. The tracking maintenance method according to claim 1, characterized in that, Step 6 includes: Step 6.1: Convert the pitch angle and other filtering information to be output from polar coordinates to the platform rectangular coordinate system, then from the platform rectangular coordinate system to the northeast-sky coordinate system, and then from the northeast-sky coordinate system to the geocentric-ground-fixed coordinate system to obtain the third offset. Step 6.2: Obtain the final geocentric solid output value based on the third offset.

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