A dual-band weak target detection method based on Hough transform

Abstract

This invention discloses a dual-band weak target detection method based on Hough transform, comprising the following steps: S1, selecting two frequency bands of radar beams, aligning the two frequency band beams spatially and temporally, and scanning the target area; S2, acquiring the echo data of the two frequency band beams, and setting initial detection thresholds for initial target detection; S3, for the two sets of echo data after the initial detection in S2, performing wide-constraint detection using pre-loaded information to select detection units that meet motion characteristic constraints; S4, for the detection units selected in S3, performing dual-frequency fusion detection based on Hough transform, and determining the target point in the parameter domain transform spectrum after Hough transform; S5, for the target point determined in S4, using inverse Hough transform to output the measurement values ​​of each dimension; This method has high efficiency and relatively stable detection performance when external interference noise conditions change significantly.

Description

Technical Field

[0001] This invention relates to the field of radar signal detection, and specifically to a dual-band weak target detection method based on Hough transform. Background Technology

[0002] With the rapid development of electronic warfare and stealth technologies, detecting stealth targets in complex battlefield environments has become a major challenge for precision guidance. Currently, single-mode detection systems suffer from numerous shortcomings due to system limitations, making it nearly impossible to meet the operational requirements of future battlefields. Existing weak target detection methods, such as patents CN103777187B and CN101216554B, suffer from problems such as considering only single-frame detection, high computational load, low efficiency, and unstable detection performance when external interference and noise conditions vary significantly.

[0003] Dual-band composite targeting is a typical form of multi-mode composite weak target detection, with dual-band active systems exhibiting significant advantages in terms of target detection independence and the flexibility of anti-jamming strategies. Furthermore, dual-band composite seekers also possess advantages in detecting stealth targets that single-mode systems lack.

[0004] The effective range of a radar seeker is determined by various parameters of the radar equation. In order to improve the detection performance against stealth targets, single-mode radar detection usually adopts methods such as increasing the peak power of the transmitter, increasing antenna efficiency, increasing duty cycle, reducing noise figure and reducing system loss to increase the radar's effective range. Some scholars have also studied how to increase the coherent accumulation time to improve the seeker's sensitivity.

[0005] To meet the requirements of precise target detection and tracking weapons in complex electromagnetic environments, the development of multi-mode composite guidance target detection and tracking technology through information fusion has become an important direction for precision guidance. Employing a dual-band active composite radar operating simultaneously in two frequency bands, fully leveraging the advantages of each band, can effectively improve target detection and tracking performance. Therefore, it is necessary to propose a dual-band weak target detection method to improve both detection efficiency and stability.

[0006] The statements herein provide only background information in relation to this invention and do not necessarily constitute prior art. Summary of the Invention

[0007] The purpose of this invention is to propose a dual-band weak target detection method based on Hough transform, thereby improving target detection efficiency and maintaining stable detection performance even when external interference noise conditions change significantly.

[0008] To achieve the above objectives, this invention proposes a dual-band weak target detection method based on Hough transform, comprising the following steps:

[0009] S1. Select the beams of two frequency bands of the radar, align the beams of the two frequency bands in space and time, and scan the target area.

[0010] S2. Acquire the echo data of the beams in the two frequency bands, and set the initial detection thresholds for the target initial detection.

[0011] S3. For the two sets of echo data after the initial detection in S2, wide-constraint detection is performed using pre-loaded information to select detection units that meet the motion characteristic constraints.

[0012] S4. For the detection units selected by S3, perform dual-frequency fusion detection based on Hough transform, and determine the target point in the parameter domain transform spectrum after Hough transform.

[0013] S5. For the target point determined in S4, use the inverse Hough transform to output the measurement values ​​of each dimension.

[0014] Preferably, step S1 specifically involves simultaneously aligning the beams of the two frequency bands with the target area and simultaneously scanning using the same timestamp as the starting time.

[0015] Preferably, in step S2, for the two sets of echo data, the initial detection threshold is set by combining a fixed threshold with CFAR detection to perform initial detection, thereby excluding detection units in the two sets of echo data that are less than the corresponding initial detection threshold.

[0016] Preferably, the initial detection threshold is in, Where α is the threshold coefficient. To estimate the interference power, x i Let N be the power of the i-th detection unit, and N be the number of detection units.

[0017] Preferably, in step S3, the target distance limit, velocity limit, and acceleration limit in two adjacent frames are selected as the target motion feature constraints.

[0018] Preferably, the speed limit is the speed limit value of the target motion, which is V. min ≤V i ≤V max V i Let V be the velocity of the target in the i-th frame. min V represents the theoretical minimum velocity of the target motion. max The theoretical maximum speed of the target motion is defined as the maximum speed; the acceleration limit is defined as the acceleration limit of the target motion.

[0019] |a i |≤a max , where a max Let a be the limit value of the acceleration of the target motion. i The acceleration of the target in the i-th frame; the target distance between two adjacent frames is limited to ΔR. min ≤ΔR i,i+1 ≤ΔR max ΔR i,i+1 Let ΔR be the distance difference between the target in frame i and frame i+1. min Let be the minimum theoretical distance of the target's motion between two adjacent frames.

[0020] ΔR max Let be the theoretical maximum distance the target can travel between two adjacent frames. T is the time interval between two adjacent frames.

[0021] Preferably, step S4 includes the following steps:

[0022] S41. Perform parameter domain Hough transform on the two sets of echo data respectively. Based on the parameter domain transform method, map the echo signal from the frequency-time domain to the distance-velocity domain. Then, fuse the distance-velocity domain spectra of different frequency bands into the same coordinate system to generate the parameter domain transform spectrum.

[0023] S42. For the parameter domain transform spectrum, divide the grid according to the range resolution and velocity resolution, and calculate the grid point intensity y. i Fill the grid;

[0024] S43. Calculate the mesh intensity threshold y r And compare y i and y r This allows us to determine the target point.

[0025] Preferably, the grid point intensity y i The calculation steps are as follows: Take N frames from the radar scan results of the two frequency band beams, and calculate the grid point intensity y. i The value of is 0 ≤ y i ≤X,y i = α1N1 + α2N2, where X is the maximum number of detectable targets, α1 is the specific weighting value for the first frequency band, n1 is the number of lines falling into the grid in n frames of the first frequency band, α2 is the specific weighting value for the second frequency band, and n2 is the number of lines falling into the grid in n frames of the second frequency band. R1 and R2 represent the maximum detection distances for the first and second frequency bands under the detection system parameters, respectively.

[0026] Preferably, in step S43, if y i <y r If y i ≥y r This indicates that there is a goal.

[0027] Compared with the prior art, the technical solution of the present invention has the following advantages and beneficial effects:

[0028] This paper proposes a dual-band weak target detection method based on Hough transform. It utilizes multi-frame data from two frequencies, undergoes parameter domain transformation, and employs a specific weighting method to identify and detect targets. Range and velocity resolutions are used to divide the parameter domain transform spectrum after Hough transform into a grid. After specific weight derivation, the intensity of each grid point is calculated, and the target is identified by comparing the intensity of each grid point with a grid threshold set by the detection system. This method first performs preliminary screening before target identification, significantly reducing the amount of data to be identified. It is highly efficient and exhibits stable detection performance even under varying external interference and noise conditions. Compared to single-frequency Hough transform detection, this method reduces the false alarm rate for the same signal detection probability.

[0029] This solution extends the traditional single-band Hough transform target detection to dual-band fusion detection, resulting in higher detection performance and better detection accuracy, while overcoming the problems of insufficient detection accuracy and poor efficiency of traditional algorithms.

[0030] This scheme obtains specific weights for the dual bands by detecting system parameters, and calculates the weighted grid strength of the dual bands in each grid, which is used as the basis for determining whether there is a target in the grid. Compared with single-band fusion, dual-band fusion eliminates more false alarms, so that under the same detection probability, dual-band fusion detection often requires a lower signal-to-noise ratio. Dual-band fusion detection increases the radar's maximum detection range, and at the same time, it makes the received signal strength stronger in the process of weak target detection. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating a dual-band weak target detection method based on Hough transform according to an embodiment of the present invention.

[0032] Figure 2 This is a schematic diagram illustrating the generation of a parameter domain transform spectrum based on two sets of echo data in an embodiment of the present invention;

[0033] Figure 3 This is a comparison chart of the detection probabilities of the method in this embodiment and the single-band detection method. Detailed Implementation

[0034] The following will be combined with the embodiments of the present invention. Figures 1-3 The technical solutions, structural features, objectives and effects achieved in the embodiments of the present invention will be described in detail.

[0035] It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions. They are only used to facilitate and clarify the purpose of illustrating the embodiments of the present invention, and are not intended to limit the implementation conditions of the present invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportional relationship, or adjustments to the size should still fall within the scope of the technical content disclosed in the present invention, provided that they do not affect the effects and objectives that the present invention can produce.

[0036] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only the expressly listed elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0037] This invention discloses a dual-band weak target detection method based on Hough transform. For multi-frame dual-frequency data, parameter domain transformation is performed. Range and velocity resolutions are used to divide the data into grids on the parameter domain transform spectrum after the Hough transform. After specific weight derivation, the intensity of each grid point is calculated, and the intensity of each grid point is compared with a threshold intensity to identify the target. This weak target detection method is highly efficient and maintains stable detection performance even under significant changes in external interference noise conditions, exhibiting good robustness.

[0038] The technical solution of the present invention will be described below with reference to specific embodiments.

[0039] like Figure 1 As shown, an embodiment of the present invention provides a dual-band weak target detection method based on Hough transform, comprising the following steps:

[0040] S1. Select the beams of two frequency bands of the radar and align the beams of the two frequency bands in space and time; specifically, align the beams of the two frequency bands with the target area at the same time and scan them simultaneously using the same timestamp as the starting time; the selection of the two frequency bands can be made according to the actual situation and the specific radar.

[0041] S2. Acquire the echo data of the beams in the two frequency bands, and set the initial detection thresholds for the target initial detection.

[0042] In this embodiment, the initial detection threshold is set by combining a fixed threshold with CFAR (constant false alarm rate) detection for initial detection. Specifically, the initial detection threshold in this embodiment is: in, Where α is the threshold coefficient. To estimate the interference power, x i Let N be the power of the i-th detection unit, and N be the number of detection units. In practice, the larger N is, the better the effect, but the amount of calculation will also increase. Therefore, the size of N can be determined according to the actual needs.

[0043] For the echo data of the two frequency band beams, the thresholds are calculated and set according to the above formulas, and the target initial detection is performed. The detection units in the two sets of echo data that are less than the corresponding initial detection thresholds are excluded. This step S2 is the preliminary screening, which initially reduces the detection data and improves the detection efficiency.

[0044] S3. For the two sets of echo data after the initial detection in S2, wide-constraint detection is performed using pre-loaded information to select detection units that meet the motion characteristic constraints.

[0045] The pre-installed information can be prior knowledge such as multi-target distance, velocity, angle, energy, and signal-to-noise ratio. In this embodiment, target distance limits, velocity limits, and acceleration limits in two adjacent frames are selected as motion feature constraints for the target. The velocity limit is the target's velocity limit value, i.e., V. min ≤V i ≤V max V i Let V be the velocity of the target in the i-th frame. min V represents the theoretical minimum velocity of the target motion. max The theoretical maximum velocity of the target motion is given by |a|, where the acceleration limit is the acceleration limit of the target motion. i |≤a max , where a max Let a be the limit value of the acceleration of the target motion. i Let be the acceleration of the target in the i-th frame, and let ΔR be the target distance between two adjacent frames. min ≤ΔR i,i+1 ≤ΔR max ΔR i,i+1 Let ΔR be the distance difference between the target in frame i and frame i+1. min Let be the minimum theoretical distance of the target's motion between two adjacent frames. ΔR max Let be the theoretical maximum distance the target can travel between two adjacent frames. T is the time interval between two adjacent frames; by filtering out the detection units that meet the motion feature constraints from the two sets of echo data, the amount of detection data can be greatly reduced and the target detection efficiency can be improved.

[0046] S4. For the two sets of detection units selected in S3, dual-frequency fusion detection is performed based on Hough transform, and the target point is determined in the parameter domain transform spectrum after Hough transform. This step S4 specifically includes the following steps:

[0047] S41. Perform parameter-domain Hough transform on the two sets of echo data respectively. Based on the parameter-domain transform method, map the echo signal from the frequency-time domain to the range-velocity domain. Then, fuse the range-velocity domain spectra of different frequency bands into the same coordinate system to generate the parameter-domain transformed spectrum. The form of the parameter-domain transform method is: ρ = μsinθ + tcosθ, where (μ, t) are the coordinates in the rectangular coordinate system, ρ is the distance from the origin to the normal to the line, and θ is the angle between the normal and the positive x-axis. Figure 2 The diagram shown is a schematic of generating a parameter domain transform spectrum based on two sets of echo data.

[0048] S42. For the parameter domain transform spectrum, divide the grid according to the range resolution and velocity resolution, and calculate the grid point intensity y. i Fill the grid;

[0049] Mesh generation is performed based on range resolution and velocity resolution, specifically including: determining the range resolution ΔR and the velocity resolution ΔV, where... B is the bandwidth of the radar signal, and c is the speed of light. λ is the radar wavelength, f r The pulse repetition frequency is defined; the system is divided into distance and velocity axes, with the distance axis having the following number of grid cells. R max To determine the maximum detection range of the radar, the number of grid cells on the velocity axis is... V max The maximum detectable velocity of the radar is given; a grid is generated on the range axis and velocity axis based on the range resolution ΔR and velocity resolution ΔV;

[0050] The grid point intensity y i The calculation steps are as follows: Take n frames from the radar scan results of the two frequency band beams, and calculate the grid point intensity y. i The value of is 0 ≤ y i ≤10 (here, 10 is the maximum number of detectable targets; in this embodiment, a maximum of 10 targets are to be detected), y i= α1n1 + α2n2, where α1 is the specific weighting value of the first frequency band, n1 is the number of lines falling into the grid in n frames of the first frequency band, α2 is the specific weighting value of the second frequency band, and n2 is the number of lines falling into the grid in n frames of the second frequency band. R1 and R2 represent the maximum detection distances for the first and second frequency bands under the given detection system parameters, respectively, and are determined by the inherent properties of the detection system. In this embodiment, n is set to 5; however, other values ​​may be used in other embodiments.

[0051] S43. Calculate the mesh intensity threshold y r And compare y i and y r This determines the target point. Specifically: if y i <y r If y i ≥y r If so, it indicates the presence of a target; the intensity threshold y of the grid. r It is determined based on the detection system itself.

[0052] S5. Use inverse Hough transform to output the measurement values ​​of each dimension;

[0053] The distance and velocity of the target point determined in step S4 are the target's distance and velocity. The target point is inversely transformed using the parameter domain formula to obtain the measurement values ​​of each dimension of the target.

[0054] By employing the technology of this invention, the detection efficiency of targets can be greatly improved, such as... Figure 3 The figure shown is a probability comparison chart of target detection using the method of the present invention (dual-frequency fusion) with single-frequency band interception and single-frequency band single frame. It can be seen that the method of the present invention significantly improves the probability of detecting targets in weak target detection.

[0055] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A dual-band weak target detection method based on Hough transform, characterized in that, Includes the following steps: S1. Select the beams of two frequency bands of the radar, align the beams of the two frequency bands in space and time, and scan the target area. S2. Acquire the echo data of the beams in the two frequency bands, and set the initial detection thresholds for the target initial detection. S3. For the two sets of echo data after the initial detection in S2, wide-constraint detection is performed using pre-loaded information to select detection units that meet the motion characteristic constraints. S4. For the detection units selected by S3, perform dual-frequency fusion detection based on Hough transform, and determine the target point in the parameter domain transform spectrum after Hough transform. S5. For the target point determined in S4, use the inverse Hough transform to output the measurement values ​​of each dimension. Step S4 includes the following steps: S41. Perform parameter domain Hough transform on the two sets of echo data respectively. Based on the parameter domain transform method, map the echo signal from the frequency-time domain to the distance-velocity domain. Then, fuse the distance-velocity domain spectra of different frequency bands into the same coordinate system to generate the parameter domain transform spectrum. S42. For the parameter domain transform spectrum, divide the grid according to the range resolution and velocity resolution, and calculate the grid point intensity y. i Fill the grid; S43. Calculate the mesh intensity threshold y r And compare y i and y r This allows us to determine the target point.

2. The dual-band weak target detection method based on Hough transform as described in claim 1, characterized in that, Step S1 specifically involves simultaneously aligning the beams of both frequency bands with the target area and simultaneously scanning using the same timestamp as the starting time.

3. The dual-band weak target detection method based on Hough transform as described in claim 1, characterized in that, In step S2, for the two sets of echo data, the initial detection threshold is set by combining fixed threshold and CFAR detection to perform initial detection, and detection units in the two sets of echo data that are less than the corresponding initial detection threshold are excluded.

4. The dual-band weak target detection method based on Hough transform as described in claim 3, characterized in that, The initial detection threshold is in, Where α is the threshold coefficient. To estimate the interference power, x i Let N be the power of the i-th detection unit, and N be the number of detection units.

5. The dual-band weak target detection method based on Hough transform as described in claim 1, characterized in that, In step S3, the target distance limit, velocity limit, and acceleration limit in two adjacent frames are selected as the target motion feature constraints.

6. The dual-band weak target detection method based on Hough transform as described in claim 5, characterized in that, The speed limit is the maximum speed of the target motion, which is V. min ≤V i ≤V max V i Let V be the velocity of the target in the i-th frame. min V represents the theoretical minimum velocity of the target motion. max The theoretical maximum velocity of the target motion is given; the acceleration limit is the acceleration limit of the target motion, which is |a|. i |≤a max , where a max Let a be the limit value of the acceleration of the target motion. i The acceleration of the target in the i-th frame; the target distance between two adjacent frames is limited to ΔR. min ≤ΔR i,i+1 ≤ΔR max ΔR i,i+1 Let ΔR be the distance difference between the target in frame i and frame i+1. min Let be the minimum theoretical distance of the target's motion between two adjacent frames. ΔR max Let be the theoretical maximum distance the target can travel between two adjacent frames. T is the time interval between two adjacent frames.

7. The dual-band weak target detection method based on Hough transform as described in claim 1, characterized in that, The grid point intensity y i The calculation steps are as follows: Take n frames from the radar scan results of the two frequency band beams, and calculate the grid point intensity y. i The value of is 0 ≤ y i ≤X,y i = α1n1 + α2n2, where X is the maximum number of detectable targets, α1 is the specific weighting value for the first frequency band, n1 is the number of lines falling into the grid in n frames of the first frequency band, α2 is the specific weighting value for the second frequency band, and n2 is the number of lines falling into the grid in n frames of the second frequency band. R1 and R2 represent the maximum detection distances for the first and second frequency bands under the detection system parameters, respectively.

8. The dual-band weak target detection method based on Hough transform as described in claim 1, characterized in that, In step S43, if y i <y r If y i ≥y r This indicates that there is a goal.

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