Method for detecting long-term signal accumulation

Abstract

The application provides a signal long-time accumulation detection method, comprising the following steps: receiving echo data, filtering and matching the received echo data, using a Fourier transform method to obtain a coherent accumulation result of each frame from the filtered and matched echo data, using a velocity interval segmentation method to correct Doppler distance of the coherent accumulation result, performing modulus superposition on the corrected Doppler distance to obtain a non-coherent accumulation result, detecting the non-coherent accumulation result, and selecting a larger non-coherent accumulation result as an output result. The signal long-time accumulation algorithm has the advantages of small calculation amount, small required cache space and the like, and is suitable for engineering application of a general detection system radar.

Description

Technical Field

[0001] This invention relates to the field of signal accumulation algorithm technology, and in particular to a method for detecting long-term signal accumulation. Background Technology

[0002] Multi-beam (DBF) radar, also known as a probing radar, is based on the core concept of "detecting everywhere at any time," providing continuous and uninterrupted multi-function coverage. The probing radar transmits a beam that evenly illuminates a wide airspace, continuously receiving signals using multiple simultaneously formed narrow beams. Unlike traditional scanning radars, probing radar does not employ beam scanning; instead, it utilizes DBF beamforming technology to simultaneously receive multiple beams, performing the same signal processing on the output of each beam. Since the target is always illuminated by the beam, theoretically, probing radar can achieve full-time, full-space surveillance of the covered airspace, accumulating and detecting targets at different data rates at varying distances. For example, at short range, the radar can accumulate fewer pulses to support the high data rate requirements of fire control systems; at medium to long range, it can accumulate more pulses to perform routine surveillance tasks. Because probing radar uses a wide-transmit, narrow-receiver technique, the transmitting antenna gain is very low, necessitating long-term signal accumulation techniques to increase the detection range.

[0003] Conventional coherent accumulation methods generally require that the Doppler frequency of the target within one resolution cell during the beam dwell time. This means the target moves at an approximately uniform radial velocity relative to the radar, and the movement of its echo envelope cannot exceed one range cell. If the observation time is long, this condition may not hold. The target energy after coherent accumulation will spread two-dimensionally across both range and Doppler cells, failing to accumulate effectively at a single point and causing signal-to-noise ratio loss. In existing long-duration accumulation algorithms, echo envelope alignment and Doppler spread compensation are key issues, but most existing methods are computationally intensive and difficult to implement in engineering. Summary of the Invention

[0004] The purpose of this invention is to provide a method for detecting long-term signal accumulation. Compared with conventional long-term accumulation algorithms, this algorithm has a significantly reduced computational load and is easy to implement in engineering.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions.

[0006] A method for detecting long-term signal accumulation includes the following steps: receiving echo data, performing matched filtering on the received echo data, using Fourier transform to obtain coherent accumulation results for each frame of the matched-filtered echo data, performing Doppler distance correction on the coherent accumulation results by segmenting the velocity intervals, performing modulus superposition on the corrected Doppler distances to obtain non-coherent accumulation results, detecting the non-coherent accumulation results, and selecting the larger non-coherent accumulation result as the output result.

[0007] As a further improvement of the present invention, the receiving echo data specifically involves calculating the radial distance of the target relative to the radar using formula (1), and then receiving the echo data using formula (2) to obtain the echo signal.

[0008] Target i relative to radar radial distance:

[0009] (1)

[0010] In the formula, t m For slow time, t m =mT, where T is the pulse repetition period. The radial distance of target i relative to the radar at any given time. Let i be the velocity of target i. Let i be the acceleration of target i;

[0011] Radar echo signal:

[0012] (2)

[0013] In the formula, For radar transmission signals in radial distance Delayed signal at the location, Where c is the carrier frequency and c is the speed of light. Let be the echo amplitude at the i-th point, m be the baseband signal of the m-th echo, and M be the m-th repetition period.

[0014] As a further improvement of the present invention, the matched filtering is specifically performed using formula (3) for matched filtering of the echo data.

[0015] (3)

[0016] In the formula: Let the magnitude of the i-th target be... Let be the radar transmitted signal function, and t be the fast time. The radial distance of target i relative to the radar at any given time. Let be the velocity of the i-th target. Let t be the acceleration of target i; m For slow time, j represents an imaginary number.

[0017] As a further improvement of the present invention, the step of using the Fourier transform method to obtain the coherent accumulation result of each frame from the matched-filtered echo data is specifically as follows:

[0018] The echo data is divided into M frames. Fourier transform is used to transform the echo signal of each frame in slow time. Within one frame, the coherent accumulation of energy is obtained, where M is a natural number greater than or equal to 1.

[0019] As a further improvement of the present invention, the coherent accumulation of energy within one frame is specifically as follows: in the data rollback of M frames, there are N repetition frequency data in each frame. The target radial velocity of the N repetition frequency data is calculated, and then the Doppler cell where the target is located is obtained, specifically as formula (4):

[0020] (4)

[0021] in, The wavelength corresponding to the working center frequency. Let v be the Doppler cell containing the target, and v be the radial velocity of the target. For the modulo operation, This is for rounding up to the nearest integer.

[0022] As a further improvement of the present invention, the method of segmenting the coherent accumulation result into velocity intervals for Doppler distance correction specifically includes:

[0023] Interval segmentation: The velocity interval of the echo data after coherent accumulation is segmented to obtain G velocity intervals, where G is a natural number greater than or equal to 1;

[0024] Calculation of segmented Doppler channels: Calculate the number of Doppler channels corresponding to the center velocity of each velocity interval;

[0025] Distance correction for the Doppler channel: Calculate the offset required to shift the echo data of the first frame based on the center velocity of each velocity interval. And the corresponding number of Doppler channels, and then correction is performed.

[0026] As a further improvement of the present invention, the step of segmenting the interval specifically involves radially displacing the echo data accumulated by coherence, and segmenting the interval within the velocity range according to the radial displacement.

[0027] As a further improvement of the present invention, the step adopts a segmented velocity interval method to perform Doppler distance correction, and then performs modulus superposition of the corrected Doppler distances to obtain a noncoherent accumulation result, specifically as follows:

[0028] After the echo data passes through m frames, the radial displacement of the target is obtained according to formula (5), specifically:

[0029] (5)

[0030] Where m is the mth echo baseband signal, N is the number of echoes in a single frame, T represents the pulse repetition period, and v represents the target velocity.

[0031] Let the length of the radar's range resolution cell be... , R m The displacement of the m-th target is represented by the number of distance units of the displacement, which is rounded up to formula (6).

[0032] (6)

[0033] The possible velocity range of the target is divided into fixed steps, and the step is defined by formula (7).

[0034] (7)

[0035] In formula (7), K is the number of repetitions in a single frame;

[0036] Suppose that the possible speed range of the target is divided into G speed intervals, and the center speed of the g-th speed interval is... , then according to Calculate the offset that the data in frame m needs to be shifted. Expressed by formula (8);

[0037] (8)

[0038] The corresponding number of Doppler channels is expressed by formula (9):

[0039] (9)

[0040] Then, a modulo operation is performed on the coherent accumulation results of M frames, using the last frame's data as a reference, based on... Doppler channel in frame m Displacement in distance The data after shifting M frames is accumulated to complete the non-coherent accumulation.

[0041] As a further improvement of the present invention, selecting a larger noncoherent accumulation result as the output result specifically means: in the corresponding Doppler channel Performing CFAR calculations yields the detection result at the current speed. This process is repeated for each of the G speed intervals to obtain the detection results for those G speed intervals. Finally, the final detection result is obtained by performing a maximum value operation on the G detection results.

[0042] As a further improvement of the present invention, the noncoherent accumulation specifically involves shifting the Doppler channel upwards and accumulating the shifted data.

[0043] The beneficial effects of this invention are as follows:

[0044] This invention provides a long-term accumulation algorithm suitable for engineering applications. First, it performs coherent accumulation across M frames, increasing the Doppler tolerance by a factor of M. For most targets, the Doppler velocity can be approximated as constant during the accumulation time. Then, it divides velocity intervals according to the range cell length and calculates the displacement corresponding to the center velocity of each velocity interval within each frame. This displacement aligns the range cells of the corresponding Doppler channels within each frame, achieving range migration compensation. This range migration compensation method is simple and computationally inexpensive. Next, it superimposes the data from the corresponding Doppler channels across multiple frames to achieve non-coherent accumulation. The non-coherent accumulation result is then subjected to range-dimensional CFAR, and the CFAR results from multiple velocity intervals are selected from a certain range to obtain the final detection result. Besides the original data, each computation only needs to cache the CFAR result of the current range-velocity interval, thus requiring less storage space. In summary, this long-term signal accumulation algorithm has advantages such as low computational complexity and small cache space requirement, making it suitable for engineering applications of radar systems with broad detection capabilities. Attached Figure Description

[0045] Figure 1 The flowchart is a method for detecting long-term signal accumulation provided by the present invention. Detailed Implementation

[0046] The present invention will now be described in detail with reference to various embodiments. However, it should be noted that these embodiments are not intended to limit the present invention. Equivalent changes or substitutions in function, method, or structure made by those skilled in the art based on these embodiments are all within the protection scope of the present invention.

[0047] See attached document Figure 1As can be seen, the method for detecting long-term signal accumulation in this embodiment includes the following steps: receiving echo data, performing matched filtering on the received echo data, using Fourier transform to obtain coherent accumulation results for each frame of the matched filtered echo data, performing Doppler distance correction on the coherent accumulation results by segmenting the velocity interval, performing modulus superposition on the corrected Doppler distances to obtain non-coherent accumulation results, detecting the non-coherent accumulation results, and selecting the larger non-coherent accumulation result as the output result.

[0048] Specifically, the detailed steps of the above method are as follows:

[0049] First, regarding echo data, the specific method for receiving echo data is to calculate the radial distance of the target relative to the radar using formula (1), and then use formula (2) to receive the echo data to obtain the echo signal.

[0050] Target i relative to radar radial distance:

[0051] (1)

[0052] In the formula, t m For slow time, t m =mT, where T is the pulse repetition period. The radial distance of target i relative to the radar at time v i Let i be the velocity of target i. Let i be the acceleration of target i;

[0053] Radar echo signal:

[0054] (2)

[0055] In the formula, For radar transmission signals in radial distance Delayed signal at the location, Where c is the carrier frequency and c is the speed of light. Let be the echo amplitude at the i-th point, m be the baseband signal of the m-th echo, and M be the m-th repetition period.

[0056] In order to obtain better echo data, it is necessary to perform corresponding matched filtering to remove impurities. Specifically, the matched filtering is performed using formula (3) to match the echo data.

[0057] (3)

[0058] In the formula: A i Let the magnitude of the i-th target be... Radar transmit signal function, where t is fast time. The radial distance of target i relative to the radar at any given time. Let be the velocity of the i-th target. Let t be the acceleration of target i; m For slow time, j represents an imaginary number.

[0059] To transform the data from the time domain to the frequency domain, a Fourier transform is performed, followed by corresponding coherent accumulation. In this method, the specific steps for obtaining the coherent accumulation result for each frame by using the Fourier transform method on the matched-filtered echo data are as follows:

[0060] The echo data is divided into M frames. Fourier transform is used to transform the echo signal of each frame in slow time. Within one frame, the coherent accumulation of energy is obtained, where M is a natural number greater than or equal to 1.

[0061] Specifically, the coherent accumulation of energy within a frame is as follows: In the data rollback of M frames, there are N repetition frequency data in each frame. The radial velocity of the target is calculated from the N repetition frequency data, and then the Doppler cell where the target is located is obtained, specifically as shown in formula (4):

[0062] (4)

[0063] in, The wavelength corresponding to the working center frequency. Let v be the Doppler cell containing the target, and v be the radial velocity of the target. For the modulo operation, This is for rounding up to the nearest integer.

[0064] To obtain better data, distance correction is required. The coherent accumulation results are segmented into velocity intervals for Doppler distance correction, specifically including:

[0065] Interval segmentation: The velocity interval of the echo data after coherent accumulation is segmented to obtain G velocity intervals, where G is a natural number greater than or equal to 1;

[0066] Calculation of Doppler channels after segmentation: Calculate the number of Doppler channels corresponding to the center velocity of each velocity interval;

[0067] Distance correction for the Doppler channel: Calculate the offset required to shift the echo data of the first frame based on the center velocity of each velocity interval. And the corresponding number of Doppler channels, and then correction is performed.

[0068] Furthermore, the step of segmenting the interval specifically involves radially displacing the echo data accumulated through coherent coherence, and segmenting the interval within the velocity range based on the radial displacement. This radial displacement compensation of the echo data accumulated through coherence within the designed velocity range can improve the signal-to-noise ratio of the corresponding velocity target and increase the target detection probability.

[0069] Furthermore, the step employs a segmented velocity interval method for Doppler distance correction, and then performs modulo summation on the corrected Doppler distances to obtain a noncoherent accumulation result, specifically as follows:

[0070] After the echo data passes through m frames, the radial displacement of the target is obtained according to formula (5), specifically:

[0071] (5)

[0072] Where m is the mth echo baseband signal, N is the number of echoes in a single frame, T represents the pulse repetition period, and v represents the target velocity.

[0073] Let the length of the radar's range resolution cell be... , R m The displacement of the m-th target is represented by the number of distance units of the displacement, which is rounded up to formula (6).

[0074] (6)

[0075] The possible velocity range of the target is divided into fixed steps, and the step is defined by formula (7).

[0076] (7)

[0077] In formula (7), K is the number of repetitions in a single frame;

[0078] In the application of formulas (6)-(7), since the speed corresponding to the step of the speed division is, within one accumulation cycle, the target just crosses the speed corresponding to a distance unit. When searching with this speed as the step size, the error of distance movement compensation will never exceed half a distance unit, and effective accumulation can be carried out.

[0079] Suppose that the possible speed range of the target is divided into G speed intervals, and the center speed of the g-th speed interval is... , then according to Calculate the offset that the data in frame m needs to be shifted. Expressed by formula (8);

[0080] (8)

[0081] The corresponding number of Doppler channels is expressed by formula (9):

[0082] (9)

[0083] Then, a modulo operation is performed on the coherent accumulation results of M frames, using the last frame's data as a reference, based on... Doppler channel in frame m Displacement in distance The data after shifting M frames is accumulated to complete the non-coherent accumulation.

[0084] In this embodiment, selecting a larger noncoherent accumulation result as the output result specifically means: in the corresponding Doppler channel Performing CFAR calculations yields the detection result at the current speed. This process is repeated for each of the G speed intervals to obtain the detection results for those G speed intervals. Finally, the final detection result is obtained by performing a maximum value operation on the G detection results.

[0085] During the calculation, the non-coherent accumulation specifically involves shifting the Doppler channel upwards and accumulating the shifted data.

[0086] Specifically, the noncoherent accumulation involves shifting the Doppler channel upwards and accumulating the shifted data.

[0087] In this embodiment, when performing non-parametric data superposition, the Doppler and range information of the obtained target echo data are used to estimate the possible range of the target velocity through Doppler. Based on the possible target velocity and interval time, the target displacement is estimated. The range is corrected through the possible displacement, and the range-corrected data from multiple frames are superimposed.

[0088] In this embodiment, the coherent results can extract the Doppler information of the target, obtain the possible velocity range of the target through Doppler, perform segmented discretization of the velocity range, and perform distance correction on each possible velocity.

[0089] This invention provides a long-term accumulation algorithm suitable for engineering applications, which solves the problem of excessive computation and storage in general algorithms. The algorithm has been tested in practice and has good working results.

[0090] In this embodiment, the displacement is measured in distance cells as the minimum resolution, and the displacement may be N distance cells. The long-term accumulation algorithm used in this embodiment includes many methods, each with varying computational complexity. Many achieve distance correction through Keystone transform and Radon-Fourier transform, which are coherent accumulation methods. Theoretically, these methods offer good accumulation results, but their Doppler tolerance is relatively low, easily leading to a decrease in signal-to-noise ratio due to target motion mismatch. These methods also require searching for target motion parameters, and each search necessitates a coherent accumulation. Therefore, the computational complexity is relatively high, but the computational complexity varies between different algorithms, making it difficult to calculate precisely.

[0091] The detailed descriptions listed above are merely specific descriptions of feasible embodiments of the present invention and are not intended to limit the scope of protection of the present invention. All equivalent embodiments or modifications made without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

[0092] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0093] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for detecting long-term signal accumulation, characterized in that, The process includes the following steps: receiving echo data, performing matched filtering on the received echo data, using Fourier transform to obtain coherent accumulation results for each frame of the matched filtered echo data, performing Doppler distance correction on the coherent accumulation results by segmenting the velocity intervals, performing modulus superposition on the corrected Doppler distances to obtain non-coherent accumulation results, detecting the non-coherent accumulation results, and selecting the larger non-coherent accumulation result as the output result. The method of segmenting the coherent accumulation results for Doppler distance correction specifically includes: segmentation: dividing the velocity interval of the echo data after coherent accumulation into G segments, where G is a natural number greater than or equal to 1; Doppler channel calculation after segmentation: calculating the number of Doppler channels corresponding to the center velocity of each velocity interval; Doppler channel distance correction: calculating the offset required to shift the echo data of the first frame based on the center velocity of each velocity interval. And the corresponding number of Doppler channels, and then perform correction; The step of segmenting the interval specifically involves radially displacing the echo data accumulated through coherent correlation, and segmenting the interval within the velocity range based on the radial displacement. The step involves segmenting the velocity interval for Doppler distance correction, and then performing modulus-based superposition of the corrected Doppler distances to obtain a non-coherent accumulation result. Specifically: After the echo data passes through m frames, the radial displacement of the target is obtained according to formula (5), specifically: （5） Where m is the mth echo baseband signal, N is the number of echoes in a single frame, T represents the pulse repetition period, and v represents the target velocity. Let the length of the radar's range resolution cell be... , R m The displacement of the m-th target is represented by the number of distance units of the displacement, which is rounded up to formula (6). （6） The possible velocity range of the target is divided into fixed steps, and the step is defined by formula (7). （7） In formula (7), K is the number of repetitions in a single frame; Suppose that the possible speed range of the target is divided into G speed intervals, and the center speed of the g-th speed interval is v. g Then according to v g Calculate the offset that the data in frame m needs to be shifted. Expressed by formula (8); （8） v g The corresponding number of Doppler channels is expressed by formula (9): （9） Then, a modulo operation is performed on the coherent accumulation results of M frames, using the last frame data as a reference, based on... In the Doppler channel of the m-th frame Displacement in distance Then, the data after the M frames are shifted are accumulated to complete the non-coherent accumulation; The specific step of selecting a larger noncoherent accumulation result as the output is: in the corresponding Doppler channel... By performing CFAR calculation, the detection result at the current speed can be obtained. By performing the above operation on G speed intervals respectively, the detection results of G speed intervals can be obtained. By performing the maximum value operation on the G detection results, the final detection result can be obtained. The noncoherent accumulation specifically involves shifting the Doppler channel upwards and accumulating the shifted data.

2. The method for detecting long-term signal accumulation according to claim 1, characterized in that, The specific method for receiving echo data is to calculate the radial distance of the target relative to the radar using formula (1), and then use formula (2) to receive the echo data to obtain the echo signal. Target i relative to radar radial distance: （1） In the formula, t m For slow time, t m =mT, where T is the pulse repetition period. for The radial distance of target i relative to the radar at time v i Let i be the velocity of target i. Let i be the acceleration of target i; Radar echo signal: （2） In the formula, For radar transmission signals in radial distance Delayed signal at the location, Where c is the carrier frequency and c is the speed of light. Let be the echo amplitude at the i-th point, m be the baseband signal of the m-th echo, and M be the m-th repetition period.

3. The method for detecting long-term signal accumulation according to claim 2, characterized in that, The matched filtering specifically involves using formula (3) to perform matched filtering on the echo data. (3) In the formula: Let the magnitude of the i-th target be... Let be the radar transmitted signal function, and t be the fast time. for The radial distance of target i relative to the radar at any given time. Let be the velocity of the i-th target. Let t be the acceleration of target i; m For slow time, j represents an imaginary number.

4. The method for detecting long-term signal accumulation according to claim 1, characterized in that, The specific steps for obtaining the coherent accumulation result of each frame by using the Fourier transform method on the matched-filtered echo data are as follows: The echo data is divided into M frames. Fourier transform is used to transform the echo signal of each frame in slow time. Within one frame, the coherent accumulation of energy is obtained, where M is a natural number greater than or equal to 1.

5. The method for detecting long-term signal accumulation according to claim 4, characterized in that, The coherent accumulation of energy within a frame is specifically achieved by calculating the target radial velocity based on the N repetition frequency data in each frame of the M-frame data rollback, thereby obtaining the Doppler cell where the target is located, as specified in formula (4): (4) in, The wavelength corresponding to the working center frequency. Let v be the Doppler cell containing the target, and v be the radial velocity of the target. For the modulo operation, This is for rounding up to the nearest integer.

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