Shipborne navigation radar echo stabilizing method based on image processing

Abstract

The invention discloses a shipborne navigation radar echo stabilization method based on image processing. The method comprises the following steps: step 1, synchronously obtaining real-time echo data of a radar and real-time motion data of a ship where the radar is located; 2, generating a radar real-time echo image and correcting the orientation; step 3, clutter filtering is carried out; 4, judging whether drawing is performed for the first time or not; 5, aligning the previous frame of radar echo image with the current frame; step 6, when drawing is carried out for the first time, assigning the current frame to the previous frame; step 7, performing weighted iteration fusion on the current frame of radar echo image and the previous frame of radar echo image subjected to affine transformation or assignment; and step 8, carrying out weighted stacking on the fused image and the current frame of radar echo image to obtain a final stable radar echo image. According to the invention, stable processing of the ship-borne navigation radar echo image can be realized, continuity and stability of the radar image are effectively improved, and powerful support is provided for ship navigation safety.

Description

Technical Field

[0001] This invention relates to the field of shipborne navigation radar data processing technology, and in particular to a shipborne navigation radar echo stabilization method based on image processing. Background Technology

[0002] With the continuous growth of maritime traffic and the increasing complexity of the navigation environment, the stability and reliability of shipborne navigation radar, as a key device for safe navigation at sea, have become particularly important. Traditional radar data processing methods have limitations in handling image jitter caused by dynamic sea clutter and ship motion, which may lead to unstable radar images and affect navigation safety.

[0003] To improve the stability of radar images, researchers have begun exploring image processing-based methods. These methods generate more stable and reliable radar images by analyzing and processing radar echo data. Image processing techniques, such as morphological operations and affine transformations, can be used to filter clutter, correct image orientation, align image frames, and fuse image information, thereby improving the quality and stability of radar images. However, their application is mostly limited to processing images with a fixed image center. Existing radar image stabilization methods still face some challenges in shipborne navigation radar data processing, such as the six degrees of freedom motion of ships, unstable target tracking, and clutter interference, which affect the stability and reliability of radar images.

[0004] Therefore, researching a new image processing-based method for stabilizing shipborne navigation radar echoes is of great significance for improving the stability and continuity of radar images. Summary of the Invention

[0005] The technical problem this invention aims to solve is to address the shortcomings of existing technologies by providing an image processing-based method for stabilizing shipborne navigation radar echoes. This method significantly improves the stability and continuity of radar images by implementing steps such as synchronous acquisition of radar echo data, image generation, clutter filtering, and image stabilization processing. This method optimizes the generation and updating process of radar images using image processing technology, ensuring the efficiency and accuracy of stable radar echo image display, providing reliable technical support for maritime navigation safety, and laying a solid foundation for real-time monitoring and application of radar images.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for stabilizing the echo of a shipborne navigation radar based on image processing includes the following steps.

[0008] Step 1: Simultaneously acquire real-time radar echo data and real-time motion data of the ship where the radar is located.

[0009] Step 2: Generate a real-time radar echo image f1 using the radar real-time echo data obtained in Step 1; and correct the azimuth of f1 based on the ship's heading information in the real-time ship motion data to obtain a radar echo image f1' in the due north direction.

[0010] Step 3: Filter out clutter from the radar echo image f1'.

[0011] Step 4: Determine whether the radar echo image f1' of the current frame is being drawn for the first time; if so, proceed to step 6; otherwise, execute step 5.

[0012] Step 5: Calculate the offset value of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′; based on this offset value, perform an affine transformation on f2′ to make f2′ spatially aligned with f1′.

[0013] Step 6: When f1' is being drawn for the first time, f1' is directly assigned to f2'.

[0014] Step 7: Perform weighted iterative fusion of the current frame radar echo image f1' with the previous frame radar echo image f2' after affine transformation or assignment to form the fused previous frame radar echo image f2″.

[0015] Step 8: Weighted superposition of f2″ and f1' to obtain the final stable radar echo image f.

[0016] In step 7, the formula for calculating f2″ is:

[0017] f2″=f2′*k+f1′*(1-k)

[0018] Where k is the iteration coefficient, k∈[0,1].

[0019] The iteration coefficient k needs to be determined based on the state of the ship target, specifically:

[0020] A. When the target ship is affected by six degrees of freedom motion, the value of k is directly proportional to the sea state level. The higher the sea state level, the larger the value of k.

[0021] B. When the target ship tracking is unstable or interfered with by clutter, k is taken as 0.5 to 1. By increasing the value of k, the ship target can be detected stably.

[0022] In step 8, the formula for calculating the stable radar echo image f is:

[0023] f = f2″*n + f1′*m

[0024] Where n is the weighted superposition coefficient of the previous radar echo image f2″, and n∈[-1,1].

[0025] m is the weighted superposition coefficient of the radar echo image f1' of the current frame, and m∈[-1,1].

[0026] The values ​​of n and m mentioned above are adjusted according to the actual navigation scenario, specifically as follows:

[0027] A. The actual navigation scenario is a conventional scenario, which requires stable compensation for the impact of environmental conditions on radar echoes. In this case, the iterative processing data is completely trusted, with n=1 and m=0.

[0028] B. In actual navigation scenarios where enhanced echo display and increased monitoring of maneuvering targets are required, n=1, and the setting of m is positively correlated with the target speed. The faster the target speed, the larger m becomes until it reaches 1.

[0029] C. In actual navigation scenarios where sea state is level 2 or below, target tracking is stable, and there is no clutter interference, the radar detection real-time performance is guaranteed, with n=0 and m=1.

[0030] D. In actual navigation scenarios where only fast-moving targets are considered and the echoes of fixed targets are discarded, n = -1 and m = 1.

[0031] Step 5, the method for spatial alignment of f2′ and f1′, specifically includes the following steps:

[0032] Step 5.1: Obtain the real-time positioning data of the ship where the radar is located, including latitude and longitude data.

[0033] Step 5.2: Calculate the offset of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′.

[0034] Step 5.3: Based on the offset value obtained in step 5.2, perform an affine transformation on f2′ to align f2′ with f1′ in space.

[0035] In step 5-2, the center points of f2′ and f1′ are latitude and longitude data in ideal coordinates; the offset value is the relative distance and azimuth offset, which is obtained by converting the center point of f2′ to polar coordinates with the center point of f1′ as the origin, and obtaining the relative distance and azimuth offset of the center point of f2′ relative to the origin.

[0036] In step 5-2, the formula for calculating the relative distance-azimuth offset d is:

[0037] d = R·c

[0038] in:

[0039]

[0040] In the formula, R is the Earth's radius.

[0041] c is the central angle between the center points of f2′ and f1′.

[0042] a is a measure of the positional difference between the center points of f2′ and f1′.

[0043] φ1 and φ2 are the latitudes of the center points of f1′ and f2′, respectively, in radians.

[0044] Δφ and Δλ are the difference in latitude and longitude between the center points of f2′ and f1′, respectively.

[0045] In step 3, morphological opening operation is used to filter out clutter from the radar echo image f1'.

[0046] Step 3, which uses morphological opening operations to filter out clutter in radar echo image f1', includes the following steps:

[0047] Step 3.1: Binarize the radar echo image f1' to obtain image I.

[0048] Step 3.2: Perform erosion operation on image I.

[0049] Step 3.3: Perform a dilation operation on the image I after the erosion operation.

[0050] Step 3.4: Using the image I after the dilation operation as a mask, traverse the original radar echo image f1', set the coordinates of 0 in image I to 0 in image f1', and retain the original amplitude of the coordinates of 1 in image I in image f1', thus generating a new radar echo image f1'.

[0051] The present invention has the following beneficial effects:

[0052] 1. This invention achieves the effective execution of key steps such as synchronous acquisition of radar echo data, image generation, clutter filtering, and image stabilization through a carefully designed image stabilization framework.

[0053] 2. This invention optimizes the generation and updating process of radar images using image processing technology, significantly improving the stability and continuity of radar echo images, and providing reliable technical support for maritime navigation safety and real-time monitoring of radar images. Verification using actual navigation data has proven the effectiveness and superiority of this method in terms of image stability and accuracy, providing a trustworthy image processing method for related fields. Attached Figure Description

[0054] Figure 1 The flowchart of an image processing-based shipborne navigation radar echo stabilization method according to the present invention is shown.

[0055] Figure 2A schematic diagram of the real-time radar echo image before processing according to the present invention is shown.

[0056] Figure 3 A schematic diagram of the real-time radar echo image processed by the present invention is shown. Detailed Implementation

[0057] The present invention will now be described in further detail with reference to the accompanying drawings and specific preferred embodiments.

[0058] like Figure 1 As shown, a shipborne navigation radar echo stabilization method based on image processing includes the following steps.

[0059] Step 1: Simultaneously acquire real-time radar echo data and real-time motion data of the vessel where the radar is located to provide basic information for subsequent image generation and stabilization processing. The real-time vessel motion data mainly includes the vessel's real-time latitude and longitude, heading, speed over land, and heading over land.

[0060] Step 2: Using the real-time radar echo data obtained in Step 1, generate as follows: Figure 2 The radar real-time echo image f1 shown is in sea state 4, with the ship rolling at an angle of 10.2°. Severe random clutter from the waves results in a low signal-to-noise ratio, making it impossible to quickly distinguish the four fixed targets in the upper right corner of the image. Based on the ship's heading information from the real-time motion data, f1 is corrected for its azimuth, thus obtaining the radar echo image f1' pointing due north.

[0061] Step 3: Preferably, morphological opening operation is used to filter out clutter bright spots in the radar echo image f1', which preferably includes the following steps.

[0062] Step 3.1: Binarize the radar echo image f1' to obtain image I.

[0063] Step 3.2: Perform an erosion operation on image I, with the mathematical definition as follows:

[0064]

[0065] Here, B is the structuring element, a small matrix, such as a 3x3 or 5x5 rectangle or circle. s and t are used to represent the horizontal and vertical indices of elements in matrix B.

[0066] The erosion of image I at point (x,y) is the smallest pixel value among all pixels covered by structuring element B after it has been translated to that position. In a binary image, if B extends beyond the foreground region at any point, that point is set to a background value of 0.

[0067] Step 3.3: Perform a dilation operation on the image I after the erosion operation, with the mathematical definition as follows:

[0068]

[0069] The dilation of image I at point (x,y) is the largest pixel value among all pixels covered by structuring element B after translating it to that position. In a binary image, if B overlaps with the foreground region at any point, that point is set to 1.

[0070] Step 3.4: Using the image I after the dilation operation as a mask, traverse the original radar echo image f1'. Set the coordinates of points with a value of 0 in image I to 0 in image f1', and retain the original amplitude of the coordinates of points with a value of 1 in image I in image f1', generating a new radar echo image f1'. The amplitude at point (x,y) in image f1' is f'. 1(x,y) The mathematical definition of computation is as follows:

[0071] f' 1(x,y) =I (x,y) ×f' 1(x,y)

[0072] Step 4: Determine whether the radar echo image f1' of the current frame is being drawn for the first time; if so, proceed to step 6; otherwise, execute step 5.

[0073] Step 5: Calculate the offset value of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′; based on this offset value, perform an affine transformation on f2′ to make f2′ spatially aligned with f1′.

[0074] The method for spatial alignment of f2′ and f1′ described above preferably includes the following steps.

[0075] Step 5.1: Obtain the real-time positioning data of the ship where the radar is located, including latitude and longitude data.

[0076] Step 5.2: Calculate the offset of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′. Here, both the center points f2′ and f1′ are latitude and longitude data in ideal coordinates; the offset is the relative range-azimuth offset, specifically obtained by converting the center point f2′ to polar coordinates with the center point f1′ as the origin. The formula for calculating the relative range-azimuth offset d (in the WGS84 Earth coordinate system) of the center point f2′ relative to the origin is as follows:

[0077] d = R·c

[0078] in:

[0079]

[0080] In the formula, R is the Earth's radius.

[0081] c is the central angle between the center points of f2′ and f1′.

[0082] a is a measure of the positional difference between the center points of f2′ and f1′.

[0083] φ1 and φ2 are the latitudes of the center points of f1′ and f2′, respectively, in radians.

[0084] Δφ and Δλ are the difference in latitude and longitude between the center points of f2′ and f1′, respectively.

[0085] Step 5.3: Based on the offset value obtained in step 5.2, perform an affine transformation on f2′ to align f2′ with f1′ in space.

[0086] Step 6: When f1' is being drawn for the first time, f1' is directly assigned to f2'.

[0087] Step 7: Perform a weighted iterative fusion of the current frame radar echo image f1' and the previous frame radar echo image f2' (after affine transformation or assignment) to form the fused previous frame radar echo image f2″. The preferred calculation formula is:

[0088] f2″=f2′*k+f1′*(1-k)

[0089] Where k is the iteration coefficient, k∈[0,1].

[0090] The iteration coefficient k mentioned above needs to be determined based on the state of the ship target, specifically as follows:

[0091] A. When the target ship is affected by six degrees of freedom motion, the value of k is directly proportional to the sea state level. The higher the sea state level, the larger the value of k.

[0092] The six degrees of freedom motion of a ship mainly include roll, pitch, bow, heave, sway, and pitch. Roll poses the greatest threat to radar detection, with a maximum tilt angle of up to 30°. The vertical beamwidth of marine radar is generally below 25°, that is, the upper and lower boundary angles are 12.5° or less.

[0093] For example, in sea state 5, the ship's roll angle can reach 10-15°. When the ship's roll angle is greater than the upper and lower boundary angles of the vertical beam, it directly causes radar detection failure. The k value needs to be kept at 1 to compensate for echo stability. In sea states above 5, normal navigation of ships is restricted, and the k value can be kept at 1.

[0094] When navigating oceans, if the sea state is 3-4, setting k to 0.75 is optimal by default.

[0095] B. The target vessel tracking is unstable or affected by clutter.

[0096] During radar detection, interference from other radars in the same band and obstructions on the water surface may cause several periods of missing data at a certain detection radial angle, resulting in false alarms. In this case, k is set to 0.5 to 1, and the value of k is increased until the ship target can be detected stably.

[0097] Step 8: Weighted summation of f2″ and f1' to obtain the final result. Figure 3 The preferred calculation formula for the stable radar echo image f shown is:

[0098] f = f2″*n + f1′*m

[0099] Where n is the weighted superposition coefficient of the previous radar echo image f2″, and n∈[-1,1].

[0100] m is the weighted superposition coefficient of the radar echo image f1' of the current frame, and m∈[-1,1].

[0101] The values ​​of n and m mentioned above are adjusted according to the actual navigation scenario, specifically as follows:

[0102] A. The actual navigation scenario is a conventional scenario, which requires stable compensation for the impact of environmental conditions on radar echoes. In this case, the iterative data processing is completely trusted, with n=1 and m=0.

[0103] B. In actual navigation scenarios where enhanced echo display and increased monitoring of maneuvering targets are required, n=1, and the setting of m is positively correlated with the target speed. The faster the target speed, the larger m becomes until it reaches 1.

[0104] C. In actual navigation scenarios where sea state is level 2 or below, target tracking is stable, and there is no clutter interference, the radar detection real-time performance is guaranteed, with n=0 and m=1.

[0105] D. In actual navigation scenarios where only fast-moving targets are considered and the echoes of fixed targets are discarded, n = -1 and m = 1.

[0106] Figure 2 The sea state was 4, with the ship rolling at 10.2°. Severe random clutter from the waves resulted in a low signal-to-noise ratio, making it impossible to quickly distinguish the four fixed targets in the upper right corner of the image. After processing with this method, the random clutter from the waves in the right half of the image was significantly reduced, the targets and echoes became fuller and more solid, and the echo quality was significantly improved. Specifically, as shown below... Figure 3 As shown.

[0107] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the protection scope of the present invention.

Claims

1. A method for stabilizing the echo of a shipborne navigation radar based on image processing, characterized in that: Includes the following steps: Step 1: Simultaneously acquire real-time radar echo data and real-time motion data of the ship where the radar is located; Step 2: Generate a real-time radar echo image f1 using the radar real-time echo data obtained in Step 1; and correct the azimuth of f1 based on the ship's heading information in the real-time ship motion data to obtain a radar echo image f1' in the due north direction. Step 3: Filter out clutter from the radar echo image f1'; Step 4: Determine whether the radar echo image f1' of the current frame is being drawn for the first time; if so, proceed to step 6; otherwise, execute step 5. Step 5: Calculate the offset of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′; Based on this offset value, perform an affine transformation on f2′ to align f2′ with f1′ in space; Step 6: When f1' is being drawn for the first time, assign f1' directly to f2'; Step 7: Perform weighted iterative fusion of the current frame radar echo image f1' with the previous frame radar echo image f2' after affine transformation or assignment to form the fused previous frame radar echo image f2″. Step 8: Weighted superposition of f2″ and f1' to obtain the final stable radar echo image f.

2. The image processing-based shipborne navigation radar echo stabilization method according to claim 1, characterized in that: In step 7, the formula for calculating f2″ is: f2″=f2′*k+f1′*(1-k) Where k is the iteration coefficient, k∈[0,1].

3. The image processing-based shipborne navigation radar echo stabilization method according to claim 2, characterized in that: The iteration coefficient k needs to be determined based on the state of the ship target, specifically: A. When the target ship is affected by six degrees of freedom motion, the value of k is directly proportional to the sea state level. The higher the sea state level, the larger the value of k. B. When the target ship tracking is unstable or interfered with by clutter, k is taken as 0.5 to 1. By increasing the value of k, the ship target can be detected stably.

4. The image processing-based shipborne navigation radar echo stabilization method according to claim 1, characterized in that: In step 8, the formula for calculating the stable radar echo image f is: f = f2″*n + f1′*m Where n is the weighted superposition coefficient of the previous radar echo image f2″, and n∈[-1,1]; m is the weighted superposition coefficient of the radar echo image f1' of the current frame, and m∈[-1,1].

5. The image processing-based shipborne navigation radar echo stabilization method according to claim 1, characterized in that: The values ​​of n and m are adjusted according to the actual navigation scenario, specifically as follows: A. The actual navigation scenario is a conventional scenario, and it is necessary to stably compensate for the impact of environmental conditions on radar echoes. In this case, the iterative data processing is completely trusted, with n=1 and m=0. B. In actual navigation scenarios where enhanced echo display and increased monitoring of maneuvering targets are required, n=1, and the setting of m is positively correlated with the target speed. The faster the target speed, the larger m becomes until it reaches 1. C. When the actual navigation scenario is sea state 2 or below, target tracking is stable and there is no clutter interference, ensure the real-time performance of radar detection, n=0, m=1; D. In actual navigation scenarios where only fast-moving targets are considered and the echoes of fixed targets are discarded, n = -1 and m = 1.

6. The image processing-based shipborne navigation radar echo stabilization method according to claim 1, characterized in that: Step 5, the method for spatial alignment of f2′ and f1′, specifically includes the following steps: Step 5.1: Obtain the real-time positioning data of the ship where the radar is located, including latitude and longitude data; Step 5.2: Calculate the offset of the center point of the previous radar echo image f2′ relative to the center point of the current radar echo image f1′; Step 5.3: Based on the offset value obtained in step 5.2, perform an affine transformation on f2′ to align f2′ with f1′ in space.

7. The image processing-based shipborne navigation radar echo stabilization method according to claim 6, characterized in that: In step 5-2, the center points of f2′ and f1′ are latitude and longitude data in ideal coordinates; the offset value is the relative distance and azimuth offset, which is obtained by converting the center point of f2′ to polar coordinates with the center point of f1′ as the origin, and obtaining the relative distance and azimuth offset of the center point of f2′ relative to the origin.

8. The image processing-based shipborne navigation radar echo stabilization method according to claim 7, characterized in that: In step 5-2, the formula for calculating the relative distance-azimuth offset d is: d = R·c in: In the formula, R is the Earth's radius; c is the central angle between the center points of f2′ and f1′; a is a measure of the positional difference between the center points of f2′ and f1′; φ1 and φ2 are the latitudes of the center points of f1′ and f2′, respectively, in radians; Δφ and Δλ are the difference in latitude and longitude between the center points of f2′ and f1′, respectively.

9. The image processing-based shipborne navigation radar echo stabilization method according to claim 1, characterized in that: In step 3, morphological opening operation is used to filter out clutter from the radar echo image f1'.

10. The image processing-based shipborne navigation radar echo stabilization method according to claim 9, characterized in that: Step 3, which uses morphological opening operations to filter out clutter in radar echo image f1', includes the following steps: Step 3.1: Binarize the radar echo image f1' to obtain image I; Step 3.2: Perform erosion operation on image I; Step 3.3: Perform a dilation operation on image I after the erosion operation; Step 3.4: Using the image I after the dilation operation as a mask, traverse the original radar echo image f1', set the coordinates of 0 in image I to 0 in image f1', and retain the original amplitude of the coordinates of 1 in image I in image f1', thus generating a new radar echo image f1'.

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