CN108562879B - Constant false alarm detection method for ship-borne radar based on FPGA - Google Patents

Constant false alarm detection method for ship-borne radar based on FPGA Download PDF

Info

Publication number
CN108562879B
CN108562879B CN201810350034.1A CN201810350034A CN108562879B CN 108562879 B CN108562879 B CN 108562879B CN 201810350034 A CN201810350034 A CN 201810350034A CN 108562879 B CN108562879 B CN 108562879B
Authority
CN
China
Prior art keywords
range
clutter
zero
false alarm
constant false
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810350034.1A
Other languages
Chinese (zh)
Other versions
CN108562879A (en
Inventor
王昊
丁施健
丁睿
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xiangyang Technology (Nantong) Co.,Ltd.
Original Assignee
Nanjing University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Science and Technology filed Critical Nanjing University of Science and Technology
Priority to CN201810350034.1A priority Critical patent/CN108562879B/en
Publication of CN108562879A publication Critical patent/CN108562879A/en
Application granted granted Critical
Publication of CN108562879B publication Critical patent/CN108562879B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G01S7/4004—Means for monitoring or calibrating of parts of a radar system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention discloses a constant false alarm detection method for a ship-borne radar based on an FPGA. The method firstly selects different constant false alarm processing modes according to the characteristics of the transmitted waveform of the navigation radar under different measuring ranges and by combining the Doppler characteristics of the sea clutter. Because a large amount of low-speed clutter exists in the near-range zero-speed channel, clutter map constant false alarm detection is adopted; the clutter power of the near-range non-zero-speed channel and the far-range channel is low, and unit average constant false alarm detection is adopted. Under different sea conditions, the echo signal-to-clutter ratios are not consistent, and the signal power is weighted by using a parameter issuing method, so that the purposes of amplifying weak targets and suppressing strong clutter are achieved. And a target extraction algorithm is used for solving the problems of precision reduction caused by target broadening and false targets caused by data splicing. In the clutter map updating process, the influence of the ship motion on the clutter map updating is considered, and the azimuth and the distance of the clutter map are compensated.

Description

Constant false alarm detection method for ship-borne radar based on FPGA
Technical Field
The invention belongs to radar signal processing, and particularly relates to a constant false alarm detection method for a ship-borne radar based on an FPGA.
Background
The constant false alarm detection includes CFAR detection in the receiver noise and CFAR detection in the clutter background. The general CFAR includes three algorithms, namely, a CFAR algorithm based on a clutter map, a CFAR based on unit averaging, and a CFAR algorithm based on noise detection.
The clutter map technology is a constant false alarm technology which stores background clutter in real time and updates clutter power in real time in different scanning periods to determine a detection threshold, and the core of the technology is clutter average power estimation. In general, among a plurality of adjacent pulses, the sea wave clutter correlation is strong, so the effect of directly adopting a processing method of inter-pulse accumulation is not good enough. For the ship-based radar, the time interval between different times of scanning of the antenna is long (in seconds), and the correlation of the same clutter unit between two adjacent scanning periods is weak. The clutter map constant false alarm technology uses inter-circle accumulation, can effectively inhibit background clutter, ensures the false alarm rate to be constant, and is a time domain constant false alarm detection method.
1. The west ampere electronic engineering institute, a radar clutter detection threshold self-adaptive setting method: china CN106646396A.2017-05-10. A radar clutter detection threshold self-adaptive setting method provides a method for self-adaptively adjusting a constant false alarm threshold according to clutter point trace density. The method uses the trace point density to adjust the constant false alarm threshold to suppress the strong clutter, can control the false alarm rate by changing the constant false alarm threshold, has the defect that the clutter is suppressed by only changing the threshold, and cannot effectively amplify the small target and suppress the amplitude of the strong clutter according to the clutter environment. 2. The institute of electrical and electronic engineering of Western Ann, a five dimensional dynamic stereo clutter map implementation method based on DDR 3-SDRAM: china CN104535980A.2015-04-22. A five-dimensional dynamic stereo clutter map implementation method based on DDR3-SDRAM is characterized in that a five-dimensional dynamic stereo clutter map is established through read-write control over DDR3, a PRF mode and clutter of a full Doppler channel are added for division, and the storage capacity of the clutter map is doubled. The method has the defect that the clutter units cannot be accurately updated without the clutter image circle updating method.
Along with the movement of the ship, the azimuth and the distance of the clutter units can change along with the movement of the ship body, so that the position parameters of the previous accumulated turns can not correspond to the position parameters on the current scanning turns, wherein the error of the azimuth in a near area is particularly serious.
Disclosure of Invention
The invention aims to provide a constant false alarm detection method capable of realizing a ship-based radar based on an FPGA.
The technical solution for realizing the purpose of the invention is as follows: a constant false alarm detection method based on FPGA and capable of realizing ship-borne radar comprises the following steps:
step 1, a shipborne navigation radar transmits a waveform signal;
step 2, performing pulse compression on the echo signals of the waveform signals in the step 1, rearranging the data in each coherent processing interval according to a slow time dimension, and then respectively entering a zero-speed filter and a non-zero-speed filter for filtering;
step 3, performing modular operation on the signals passing through the zero-speed filter and the non-zero-speed filter, wherein the data after the modular operation is divided into three parts, namely a far-range signal, a near-range non-zero channel signal and a near-range zero channel signal, and weighting the three parts of data after the modular operation;
step 4, carrying out unit average constant false alarm detection on the weighted far-range signal and the weighted near-range non-zero channel signal; performing clutter map detection and updating on the weighted near-range zero-channel signal;
and 5, performing point trace aggregation on the near-range zero-channel signal subjected to clutter map detection, and the far-range signal and the near-range non-zero-channel signal subjected to unit average constant false alarm detection, wherein the point trace aggregation is cancelled at the data splicing position of the far-range signal and the near-range signal, so as to obtain a combined target.
Compared with the prior art, the invention has the following remarkable advantages: (1) in the clutter map updating process, the mismatching between clutter unit distance and azimuth circle caused by the movement of the ship body is considered, a fitting algorithm of a distance number and an azimuth number in the clutter map updating process is provided, and the distance and azimuth errors are reduced to the maximum extent under the constraint of chip performance. (2) The signal strength is adaptively enhanced and attenuated by controlling the signal gain and attenuation according to the clutter power through a method of sending a weighted value under display control. (3) And the trace aggregation function is adjusted by combining the waveform characteristics, so that the distance and speed detection precision is improved.
The present invention is described in further detail below with reference to the attached drawing figures.
Drawings
FIG. 1 is a time domain diagram of a carrier-borne navigation radar transmission waveform design.
Fig. 2 is a data rearrangement structure.
Fig. 3 is a signal flow diagram of constant false alarm detection of a pulse compressed signal.
Figure 4 is a block diagram of a filtered range-doppler two-dimensional signal region.
Fig. 5 is a detailed explanation of the "issued parameter weighting method" operation mode.
Fig. 6 is a schematic diagram of position information updating of the inter-circle accumulation clutter units.
FIG. 7 is a graph showing the results of an error analysis of the distance fitting equation.
FIG. 8 is a schematic diagram of distance dimensional object merging.
FIG. 9 is a time-frequency result two-dimensional graph under simulation.
Detailed Description
A constant false alarm detection method based on FPGA and capable of realizing ship-borne radar comprises the following specific steps:
step 1, transmitting a waveform signal by a ship-based navigation radar. In a further embodiment, the transmitted waveform is a near-range simple pulse waveform (for blind compensation), a far-range modulation signal waveform (for detection), and the boundary range of the near range and the far range is [ R ] -0.5km to [ R ] km, wherein [ ] is a rounding-down operation, and R represents the theoretical waveform power coverage range. . The value of R is obtained from the radar equation:
Figure BDA0001633150830000031
in the formula, PtTo transmit peak power, GtFor transmitting antenna gain, GrFor receiving antenna gain, λ is operating wavelength, Prminσ is the equivalent radar scattering cross-sectional area of the target for the signal power received by the antenna.
In other embodiments, as shown in fig. 1, the farthest coverage distance of the far range is calculated according to the radar equation, where 3km is the boundary between the far range and the near range. The pulse width of the short range simple pulse is designed to be tsshortThe pulse repetition period of the simple pulse is set to prtshortWherein
Figure BDA0001633150830000032
The length of the blind area is within the distance which can not be observed by the radar; the pulse width of the far-range modulation pulse is set to tslongThe pulse repetition period of the modulated pulse is prtlong。prtshortLong signal truncated pre-tslongData of individual length is used for near-distance blind-fill, prtlongMiddle cut tslong～prtlongIs used for remote detection.
Step 2, performing pulse compression on the echo signals of the waveform signals in the step 1, rearranging the data in each coherent processing interval according to slow time, and then respectively entering a zero-speed filter and a non-zero-speed filter for filtering;
the data rearrangement structure is shown in fig. 2.
In a further embodiment, if the antenna beam width is θ, the pulse repetition frequency of the radar is denoted as prf, and the antenna azimuth scanning angle is ωαThe target elevation angle is thetaeNumber of pulses that can be accumulated by the antenna sweeping across the target
Figure BDA0001633150830000033
N is the number of pulses accumulated in one CPI (coherent processing interval).
And the rearranged data respectively enters a zero-speed filter and a non-zero-speed filter for filtering. The method specifically comprises the following steps: n data on each range gate
Figure BDA0001633150830000041
Order filtering in which [ ·]Is a rounding-down operation, wherein
Figure BDA0001633150830000042
The order filter comprises 1 zero-speed filter and
Figure BDA0001633150830000043
and N is the number of pulses accumulated in a coherent processing interval.
And 3, performing modular operation on the signals passing through the zero-speed filter and the non-zero-speed filter, and dividing the data after the modular operation into three parts, namely a far-range signal, a near-range non-zero channel signal and a near-range zero channel signal, by combining the graph shown in FIG. 4, and weighting the three parts of data after the modular operation. The positions of the far-range signal, the near-range non-zero channel signal and the near-range zero channel data and the Doppler channel number are inconsistent, so that the clutter is inconsistent. The near-range clutter power is higher, and the far-range small target is difficult to be found. Therefore, the three parts of data need to be weighted according to the integral signal amplitude, and the purposes of amplifying the long-distance weak target and suppressing the short-distance strong clutter are achieved.
In a further embodiment, a specific method for weighting the data of the far-range signal, the near-range non-zero channel signal and the near-range zero channel after the modulo operation is performed is as follows:
and respectively solving a power average value for the three parts of signals after filtering, respectively comparing the power average value with a set threshold value, reducing the data after modulus solving by adjusting the weighted value issued by the display control to the part of signals with the power average value larger than the threshold value, and amplifying the data after modulus solving by adjusting the weighted value issued by the display control to the part of signals with the power average value smaller than the threshold value.
In a further embodiment, referring to fig. 5, the step of amplifying/reducing the modulo data by lowering the weighting value of the Zbit issued by the display control specifically includes: the display control sends Z bit data and the modulo N bit data to the multiplier for multiplication, and M-N + M-1 bits of the output result of the multiplier are intercepted, wherein Z is an integer, M is an integer fixed value, and M is greater than or equal to 0 and less than or equal to Z. The data in the Zbit sent by the display control is equivalent to the effect that the high Z-M bit of the data plays an amplifying role on the signal and the low M bit plays a reducing role on the signal. For example, if the data transmitted by the display control is 16 bits, the 16-bit data value is 184, and if M is 4, it is equivalent to multiplying the signal by 11.5.
Step 4, with reference to fig. 3, performing unit average constant false alarm detection on the weighted far-range signal and the weighted near-range non-zero channel signal; and performing clutter map detection and updating on the weighted near-range zero channel data.
When the radar works, clutter echo amplitudes of the surrounding environment are sequentially stored according to a distance and direction two-dimensional plane. Considering that the platform on which the radar is located is moving, and the scanning period of the antenna is usually in seconds, the clutter units will shift in corresponding azimuth and distance during different scanning periods. Therefore, compensation for the orientation and distance of the clutter units is needed in the process of creating and updating the clutter map.
If the sampling rate of the pulse compressed signal is fsThe distance resolution after sampling is
Figure BDA0001633150830000044
(c is the speed of light). If the azimuth number before the target update is theta0The distance of the target from the radar is r0That is, the position information of the clutter units in the previous scanning cycle is (r)0,θ0)。
If the clutter level accumulated in the history circle is
Figure BDA0001633150830000051
The update of the cluttered cell may be accomplished using the following equation:
Figure BDA0001633150830000052
in the formula, beta is a forgetting factor, the value of beta is more than or equal to 0 and less than or equal to 1, and the value represents the update speed of the clutter map. The larger the value is, the faster the clutter map iteration is, and the clutter background stability becomes worse. k represents the number of accumulated turns and,
Figure BDA0001633150830000053
the resulting clutter level is accumulated for the current number of turns,
Figure BDA0001633150830000054
the real-time clutter level is the current number of turns,
Figure BDA0001633150830000055
clutter level accumulated for the history ring, (r)1,θ1) And position information of the clutter units of the current scanning circle number.
As shown in connection with FIG. 6, the new position coordinate is noted as (r)1,θ1) Then there is a corresponding relationship between the new and old coordinates as follows
Figure BDA0001633150830000056
Figure BDA0001633150830000057
Wherein v is the moving speed of the ship, and t is the scanning period of the antenna.
In a further embodiment, in the updating process, a formula r 'is utilized'0＝r1+vtcosθ1And linear fitting is carried out on the distance formula (1), so that the FPGA resource is saved, and meanwhile, coordinate iteration is effectively completed.
For example, typical ship speeds are around 18 knots, i.e., 9.26 m/s. The distance traveled by the ship between adjacent scan intervals was 23.15m in a 24RPM background. Assuming that the data sample rate is calculated at 25M, the range resolution is 6M, and a range of 23.15M spans 3 range gates.
The error analysis was performed on the linearly fitted formula, and the results are shown in fig. 7. The ship speed is 18 knots, and on the premise that the antenna rotating speed is 24RPM, the distance number difference between the fitted formula and the actual formula is smaller than 1 from a target beyond 48m of the ship, and the fitted formula effectively completes the iteration function.
In the formula (2), the clutter unit azimuth number of the short-distance tangential motion relative to the ship is changed obviously, and the method is not suitable for fitting by using an approximation method. The azimuth resolution in this embodiment is designed to be 1 °, and the arctan operation can be implemented by using a ROM table lookup method, and only 360 corresponding relationships need to be established. Multiplication and division and sine and cosine functions are realized by using a cordic IP core, 48bit width is supported at most, and theoretical calculation values are approached to the maximum extent.
Storing the data of the previous scanning circle number into DDR3(Double Date Rate3SDRAM), according to r1And r0、θ1And theta0Can be in a ground-to-ground correspondence in such a correspondenceAnd addressing the address to update the clutter map.
And 5, performing point trace aggregation on the near-range zero-channel signal subjected to clutter map detection, and the far-range signal and the near-range non-zero-channel signal subjected to unit average constant false alarm detection, wherein the point trace aggregation is cancelled at the data splicing position of the far-range signal and the near-range signal, so as to obtain a combined target. And 4, splicing the near-range zero-speed channel data passing through a clutter map CFAR (clutter map constant false alarm detection), the near-range non-zero-speed channel data passing through a CA-CFAR (cell average constant false alarm detection) and the far-range data passing through the CA-CFAR (cell average constant false alarm detection) according to a distance and speed relationship, performing point trace aggregation on the spliced result, and canceling the point trace aggregation on a distance dimension critical position in consideration of the influence of data weighting. Through the condensation, the target detection precision can be improved.
In some embodiments, referring to fig. 8, fig. 8 is a time-frequency two-dimensional graph after CFAR, where the abscissa is a distance unit and the ordinate is a doppler unit. The doppler dimensional data is first merged where gray and black are points that are thresholded after CFAR and white are points that are not thresholded.
Determining distance dimension threshold, linear frequency modulation signal bandwidth 10M, so the main lobe width after pulse pressure is 0.1us, adding Hamming window, broadening waveform after pulse pressure to about 1.8 times (-6dB), i.e. about 0.18us, corresponding distance units are about 5 when sampling rate is 25MHz, selecting thdis＝5。
And sequentially processing the points which pass through the threshold in each Doppler dimension according to the sequence from small to large of the distance units during combination. Let p (t1, f1) be the point of the first threshold crossing (t1 is the distance unit number, f1 is the Doppler channel number), calculate the distance unit difference Δ t between p (t1, f1) and the point of the next threshold crossing (p (t2, f2)) in the Doppler channel as abs (t1-t2), if Δ t ≦ thdisThen, the point p (t1, f1) and the point p (t2, f2) are considered to be the same target, and then the point with larger amplitude and the following points in p (t1, f1) and p (t2, f2) are selected for merging processing. If Δ t>thdisThen p (t1, f1) and p (t2, f2) are not considered to be the same target. Then p (t2, f2) is the point of a new target.
For ship-borne radarIn other words, due to the inconsistency of the transmission waveforms, the data of different signal processing flows performed on different ranges is merged with two different targets when being spliced, so that the head and the tail th of each signal section should be combineddisThe dots are un-merged.
When the distance dimension combination is carried out by the method, in order to prevent one target from being excessively widened on the distance dimension and being judged as two targets by mistake, the solution is to judge whether the target is a local extreme point (whether the amplitude is larger than the amplitude values of two adjacent distance unit points or not) and judge the target as a target point, otherwise, the target point is not the local extreme point and the target point is discarded.
The invention is further illustrated below with reference to example 1.
Example 1
In practical engineering, the transmit waveform parameters are as follows: the short-range simple pulse time width is 100ns, the pulse repetition period is 25us, the intermediate frequency is 90M, the bandwidth is 10M, and the design power coverage range is within 3 km; the time width of a linear frequency modulation signal is 20us, the pulse repetition period is 120us, the intermediate frequency is 77.5M, the bandwidth is 10M, the power coverage range is designed to be 3 km-15 km, and Gaussian white noise (the power reference of the signal is set to be 0dbw) of-30 dB relative to the signal is added to data after the slow time dimension filtering. The near-range zero-velocity target is designed to be 1500m (250 range gates), the far-range non-zero-velocity target is designed to be 7500m (1250 range gates), and the Doppler frequency shift is analyzed at the 32 th speed gate on the premise that one CPI accumulates 256 prt.
According to the final result, the target can be effectively extracted by virtue of strong clutter suppression and trace aggregation, and the strong clutter is basically filtered out.

Claims (7)

1. A constant false alarm detection method for a ship-borne radar based on an FPGA is characterized by comprising the following specific steps:
step 1, a shipborne navigation radar transmits a waveform signal, the transmitted waveform is a near-range simple pulse waveform, a far-range modulation signal waveform, and the boundary range of the near range and the far range is [ R ] -0.5km to [ R ] km, wherein [ ] is a downward rounding operation, and R represents a theoretical waveform power coverage range;
step 2, performing pulse compression on the echo signals of the waveform signals in the step 1, rearranging the data in each coherent processing interval according to a slow time dimension, and then respectively entering a zero-speed filter and a non-zero-speed filter for filtering;
step 3, performing modular operation on the signals passing through the zero-speed filter and the non-zero-speed filter, wherein the data after the modular operation is divided into three parts, namely a far-range signal, a near-range non-zero channel signal and a near-range zero channel signal, and weighting the three parts of data after the modular operation;
step 4, carrying out unit average constant false alarm detection on the weighted far-range signal and the weighted near-range non-zero channel signal; performing clutter map detection and updating on the weighted near-range zero-channel signal;
and 5, performing point trace aggregation on the near-range zero-channel signal subjected to clutter map detection, the hybrid far-range signal subjected to unit average constant false alarm detection and the near-range non-zero-channel signal, wherein the point trace aggregation is cancelled at the data splicing position of the far-range signal and the near-range signal, so as to obtain a combined target.
2. The FPGA-based ship-borne radar constant false alarm detection method of claim 1, wherein the rearranged data in the step 2 are filtered by a zero-speed filter and a non-zero-speed filter, respectively, specifically: n data on each range gate
Figure FDA0003489903690000011
Order filtering in which [ ·]Is a rounding-down operation, wherein
Figure FDA0003489903690000012
The order filter comprises 1 zero-speed filter and
Figure FDA0003489903690000013
and N is the number of pulses accumulated in a coherent processing interval.
3. The FPGA-based ship-borne radar constant false alarm detection method of claim 2, wherein the calculation formula of the number of pulses accumulated in each coherent processing interval is as follows:
Figure FDA0003489903690000014
where θ is the antenna beam width, prf is the pulse repetition frequency of the radar, ωαFor antenna azimuth scanning angle, thetaeIs the target elevation.
4. The FPGA-based ship-borne radar constant false alarm detection method of claim 1, wherein the specific method for weighting the far-range signal, the near-range non-zero channel signal and the near-range zero channel signal after the modulo operation in the step 3 is as follows:
and respectively solving a power average value for the three parts of signals after filtering, respectively comparing the power average value with a set threshold value, reducing the data after modulus solving by adjusting the weighted value issued by the display control to the part of signals with the power average value larger than the threshold value, and amplifying the data after modulus solving by adjusting the weighted value issued by the display control to the part of signals with the power average value smaller than the threshold value.
5. The FPGA-based ship-borne radar constant false alarm detection method of claim 4, wherein the modulo data is amplified/reduced by increasing/decreasing a weight value issued by display control, and specifically: the display control sends Z bit data and the modulo P bit data to the multiplier for multiplication, and M-P + M-1 bits of the output result of the multiplier are intercepted, wherein Z is an integer, M is an integer fixed value, and M is greater than or equal to 0 and less than or equal to Z.
6. The FPGA-based ship-borne radar constant false alarm detection method of claim 1, wherein the clutter map detection is performed on the weighted near-range zero channel signal in the step 4, so as to realize the update of the clutter map under the motion platform, and the update formula is as follows:
Figure FDA0003489903690000021
wherein beta is a forgetting factor, beta is more than or equal to 0 and less than or equal to 1, k represents the number of accumulated turns,
Figure FDA0003489903690000022
the resulting clutter level is accumulated for the current number of turns,
Figure FDA0003489903690000023
the real-time clutter level is the current number of turns,
Figure FDA0003489903690000024
for the level of clutter accumulated for the history loop,
Figure FDA0003489903690000025
for the currently accumulated clutter level, (r)1,θ1) Position information of clutter units for the current number of scan cycles, (r)0,θ0) For the position information of clutter units during the previous scan, θ0For the azimuth number before target update, r0For the distance between the target and the radar, the corresponding relation between the position information of the clutter unit of the current scanning circle number and the position information of the clutter unit in the previous circle scanning is as follows:
Figure FDA0003489903690000026
Figure FDA0003489903690000027
wherein v is the moving speed of the ship, and t is the scanning period of the antenna.
7. The FPGA-based shipboard radar constant false alarm of claim 6The detection method is characterized in that clutter map detection is carried out on a near-range zero-channel signal, and a formula r is utilized in the clutter map updating process under a motion platform0＝r1+vtcosθ1And fitting the distance between the new coordinate and the old coordinate, updating the angle unit of the new coordinate and the old coordinate by using a Read Only Memory (ROM) table look-up method, and finishing the fitting of the new coordinate and the old coordinate, wherein v is the moving speed of the ship and t is the scanning period of the antenna.
CN201810350034.1A 2018-04-18 2018-04-18 Constant false alarm detection method for ship-borne radar based on FPGA Active CN108562879B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810350034.1A CN108562879B (en) 2018-04-18 2018-04-18 Constant false alarm detection method for ship-borne radar based on FPGA

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810350034.1A CN108562879B (en) 2018-04-18 2018-04-18 Constant false alarm detection method for ship-borne radar based on FPGA

Publications (2)

Publication Number Publication Date
CN108562879A CN108562879A (en) 2018-09-21
CN108562879B true CN108562879B (en) 2022-03-22

Family

ID=63535637

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810350034.1A Active CN108562879B (en) 2018-04-18 2018-04-18 Constant false alarm detection method for ship-borne radar based on FPGA

Country Status (1)

Country Link
CN (1) CN108562879B (en)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109859178B (en) * 2019-01-18 2020-11-03 北京航空航天大学 FPGA-based infrared remote sensing image real-time target detection method
CN110827317B (en) * 2019-11-04 2023-05-12 西安邮电大学 Four-eye moving object detection and identification equipment and method based on FPGA
CN111175709B (en) * 2019-12-27 2023-02-24 中国电子科技集团公司第十四研究所 Error suppression-based large-range meteorological radar-oriented jigsaw method
CN111323757B (en) * 2019-12-30 2022-04-05 北京海兰信数据科技股份有限公司 Target detection method and device for marine radar
CN111538012B (en) * 2020-04-27 2022-04-15 东南大学 Self-adaptive constant false alarm detection method based on interference elimination
CN111796288B (en) * 2020-06-12 2022-04-08 中国船舶重工集团公司第七二四研究所 Clutter frequency spectrum compensation technology-based three-coordinate radar moving target processing method
CN113126054A (en) * 2021-04-09 2021-07-16 电子科技大学 Target detection method based on GPU
CN114578384B (en) * 2022-05-07 2022-09-09 成都凯天电子股份有限公司 Self-adaptive constant false alarm detection method for laser atmospheric system
CN115902873B (en) * 2022-12-21 2023-09-12 扬州宇安电子科技有限公司 Radar control early warning adjusting system and method based on Internet of things

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2078213A2 (en) * 2006-11-02 2009-07-15 Raytheon Canada Limited A moving target detector for radar systems
JP2011174872A (en) * 2010-02-25 2011-09-08 Mitsubishi Electric Corp Radar signal processor
CN104898103A (en) * 2015-06-01 2015-09-09 西安电子科技大学 Low-speed target detection method based on multichannel clutter map
CN105372636A (en) * 2015-12-14 2016-03-02 四川九洲空管科技有限责任公司 Adaptive forgetting factor-based clutter image update method and apparatus
CN106291492A (en) * 2016-07-19 2017-01-04 西安电子科技大学 A kind of adaptive targets detection method based on fine clutter map

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2412518A (en) * 2004-03-27 2005-09-28 Qinetiq Ltd Improving target detection in a radar surveillance arrangement
US8013781B2 (en) * 2008-09-24 2011-09-06 Lockheed Martin Corporation Method and apparatus for radar surveillance and detection of sea targets

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2078213A2 (en) * 2006-11-02 2009-07-15 Raytheon Canada Limited A moving target detector for radar systems
JP2011174872A (en) * 2010-02-25 2011-09-08 Mitsubishi Electric Corp Radar signal processor
CN104898103A (en) * 2015-06-01 2015-09-09 西安电子科技大学 Low-speed target detection method based on multichannel clutter map
CN105372636A (en) * 2015-12-14 2016-03-02 四川九洲空管科技有限责任公司 Adaptive forgetting factor-based clutter image update method and apparatus
CN106291492A (en) * 2016-07-19 2017-01-04 西安电子科技大学 A kind of adaptive targets detection method based on fine clutter map

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
"An improved CFAR detector for non-homogeneous clutter environment";Renli Zhang;《2010 International Symposium on Signals, Systems and Electronics》;20101021;1-4 *
"FPGA-based real-time implementation of distributed system CA-CFAR and Clutter MAP-CFAR with noncoherent integration for radar detection";Houssem Eddine Benseddik;《2012 International Conference on Multimedia Computing and Systems》;20121004;1-6 *
"一种海杂波背景下快速小目标的检测方法";刘艳苹;《舰船电子对抗》;20080630;第31卷(第3期);41-49 *
"复杂背景下的恒虚警检测方法研究";张欣;《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑》;20180415;53-67 *
"自适应恒虚警算法研究";樊小倩;《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑》;20160315;39-48 *

Also Published As

Publication number Publication date
CN108562879A (en) 2018-09-21

Similar Documents

Publication Publication Date Title
CN108562879B (en) Constant false alarm detection method for ship-borne radar based on FPGA
Colone et al. Sliding extensive cancellation algorithm for disturbance removal in passive radar
CN112098990B (en) Method for detecting and tracking medium and high speed vehicle by vehicle-mounted high-resolution millimeter wave radar
CN107688178A (en) A kind of sawtooth waveforms ranging and range rate method based on 77GHz millimetre-wave radars
JP5595496B2 (en) Radar equipment
CN105652245B (en) A kind of solid state pulse compression radar width is from covering method
CN110297233B (en) LFMCW array radar signal parallel pipelining processing method
CN108957419B (en) Asynchronous interference suppression method based on notch filtering processing
CN107271967A (en) pulse coherent transponder co-channel interference processing system
CN111736126B (en) Signal processing method based on low-cost security radar
EP4343369A2 (en) Interference signal detection method and apparatus, and integrated circuit, radio device and terminal
CN110988884A (en) Medium latitude ionosphere detection method based on high-frequency ground wave radar
Marszal et al. Distance measurement errors in silent FM-CW sonar with matched filtering
CN116660847A (en) Interference signal detection method and device
CN107861116B (en) Radar ranging optimization method
CN116520303A (en) Ship-borne ground wave radar target detection method based on self-adaptive beam RDT
CN108226875B (en) Side lobe target suppression method of simultaneous multi-beam radar
TW200819775A (en) Tracking target method of radar with frequency modulation continuous wave
CN114355328B (en) Radar signal processing method, radio signal processing method and application device
CN113985376B (en) Radar comprehensive display and control excitation system
CN113835077B (en) Search radar target detection method and system based on variable pulse repetition frequency
CN118202274A (en) Radar system, method and vehicle for detecting pedestrians
CN109343047B (en) Measurement method for improving target angle detection accuracy of pulse system measurement system
AU2012244784B2 (en) Method and device for determining and representing possible target parameters
CN201754183U (en) Navigation radar detecting system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230423

Address after: 21st Floor, Building 7, No. 58 Chongchuan Road, Economic and Technological Development Zone, Nantong City, Jiangsu Province, 226004

Patentee after: Xiangyang Technology (Nantong) Co.,Ltd.

Address before: 210094 Xuanwu District, Jiangsu, Xiaolingwei 200, Nanjing

Patentee before: NANJING University OF SCIENCE AND TECHNOLOGY