CN106603976B - Intelligent microwave frequency band radio monitoring control system - Google Patents
Intelligent microwave frequency band radio monitoring control system Download PDFInfo
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- CN106603976B CN106603976B CN201611131891.XA CN201611131891A CN106603976B CN 106603976 B CN106603976 B CN 106603976B CN 201611131891 A CN201611131891 A CN 201611131891A CN 106603976 B CN106603976 B CN 106603976B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
- H04N5/765—Interface circuits between an apparatus for recording and another apparatus
- H04N5/77—Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
Abstract
The invention discloses an intelligent microwave frequency band radio monitoring control system, which comprises: transmitting the signal to a camera of a remote monitoring point microwave transmitter through a video line; the system can transmit 1 path of video signals and 1-2 paths of audio signals for remote transmission, and corresponding to each far-end point, a corresponding number of microwave receivers are configured at the central point; a first helical antenna for transmitting signals of a microwave transmitter; transmitting the signal to an amplifier and then to a second spiral antenna of the analog microwave receiver; the analog microwave receiver is used for receiving the microwave signal transmitted by the second spiral antenna and demodulating a video signal; a television or monitor directly connected to the analog microwave receiver. The invention has the advantages of high frequency stability, small influence of environmental temperature and strong flexibility.
Description
Technical Field
The invention belongs to the field of radio monitoring control systems, and particularly relates to an intelligent microwave frequency band radio monitoring control system.
Background
At present, a microwave frequency band radio monitoring control system is not strong in flexibility by arranging a microwave transmitter and changing a frequency point, and image and accompanying sound modulation sent by the microwave transmitter does not adopt a phase-locked loop technology, so that the frequency stability is not high, and the influence of the environmental temperature is large.
In summary, the existing intelligent microwave frequency band radio monitoring control system has low frequency stability, is greatly influenced by the environmental temperature, and has weak flexibility.
Disclosure of Invention
The invention provides an intelligent microwave frequency band radio monitoring control system for solving the technical problems of low frequency stability, large influence by environmental temperature and weak flexibility of the intelligent microwave frequency band radio monitoring control system.
The technical scheme adopted by the invention for solving the technical problems in the prior art is as follows:
the invention provides an intelligent microwave frequency band radio monitoring control system, which comprises:
transmitting the signal to a camera of a remote monitoring point microwave transmitter through a video line;
the system can transmit 1 path of video signals and 1-2 paths of audio signals for remote transmission, and corresponding to each far-end point, a corresponding number of microwave receivers are configured at the central point;
a first helical antenna for transmitting signals of a microwave transmitter;
transmitting the signal to an amplifier and then to a second spiral antenna of the analog microwave receiver;
the analog microwave receiver is used for receiving the microwave signal transmitted by the second spiral antenna and demodulating a video signal;
a television or monitor directly connected to the analog microwave receiver.
Furthermore, the modulation range of the microwave transmitter is +/-100 MHz;
furthermore, the television wall equipment is connected in a unified mode, and the hard disk video recorder is connected in a unified mode to record the video.
Furthermore, the frequency point of the microwave transmitter can be changed within the range of +/-100 MHz, and the flexibility is strong.
Furthermore, the image and sound transmitted by the microwave transmitter are modulated by adopting a phase-locked loop technology, so that the frequency stability is high, and the influence of the ambient temperature is small.
Further, the camera is provided with an image transition module, and the salient rigid processing method of the image transition module comprises the following steps:
for any pixel x, calculating the certainty factor of the gray value g (x) of the pixel x to three cloud models Cl, Ct and Ch in a low gray area, a transition area and a high gray area, and recording the certainty factor as mul(x),μt(x),μh(x) (ii) a If and only if mut(x) When taking the maximum value, the pixel x is divided into the transition region, set to gTRFor the transition region image, the determination principle is formalized as follows:
after the transition region pixel set is uncertainly obtained, the gray peak value of the pixel set is calculated and used as the optimal threshold value of the segmentation image.
Further, the image information pulse coupling neural network model of the camera is as follows:
Fij[n]＝Sij；
Uij[n]＝Fij[n](1+βij[n]Lij[n])；
θij[n]＝θ0e-αθ(n-1)；
wherein, betaij[n]Is an adaptive link strength coefficient;
Sij、Fij[n]、Lij[n]、Uij[n]、θij[n]respectively, input image signal, feedback input, link input, internal activity item and dynamic threshold, NwSelecting 1-3 for the total number of pixels in the selected window W to be processed and delta as an adjustment coefficient.
Further, the camera is provided with an image enhancement module, and an image enhancement method of the image enhancement module adopts a sparse redundancy model algorithm to enhance images;
firstly, an original image is polluted by additive Gaussian noise, the polluted image is called a degraded image, and the image recovery process is the reverse process of the degraded image; assume that the degradation model of the image is:
g＝Hu+v；
the restoration model of the image is then expressed as:
due to the interference of noise, a proper and unique solution cannot be obtained, and a regularization constraint is applied to the recovery model of the image; the restoration model of the image becomes a variational model:
r (u) is a regular term that is related to the nature of the image itself.
Further, the microwave receiver is provided with a chaotic sequence generating module, and the chaotic sequence generating method of the chaotic sequence generating module comprises the following steps:
(1) inputting system parameters:
obtaining a discrete function model:
in formula (1): u (0) is an initial signal, mu is a chaotic parameter, v is a fractional order, N is a signal length, j represents the iteration of the j step, alpha (mu, v, j, N) is a discrete integral kernel, u (N) is a signal of the N step, N and N are set to be 800, m is an integer of 1, L and N;
according to the formula (1), parameters u (0), mu and v are selected;
(2) judging whether the parameters can generate chaotic signals:
the tangent map b (m) is first calculated:
and then calculating the Lyapunov exponent lambda:
the same reference numerals in the formulas (2), (3) and (1) denote the same reference numerals;
the judgment basis is as follows: calculating lambda according to the formula (1), the formula (2) and the formula (3), if the lambda is greater than 0, the chaotic signal can be generated, otherwise, the chaotic signal cannot be generated;
(3) and calculating to generate chaotic signals.
Further, in step (1), the obtaining of the discrete function model includes:
by using a fractional discrete calculus method, a classical Logistic equation is modified into the following difference equation:
in the formula (4), the reaction mixture is,
a fractional order difference operator, wherein t is 1-v, 2-v, and a is an initial point;
taking a in the formula (4) as 0, and further converting the formula (4) into a discrete function model:
further, the function model of the fractional order discrete calculus is:
in formula (4), a is an initial point, ν < 1 is a fractional order, t is a +1- ν, a +2- ν, Δ u(s) u (s +1) -u(s),
gamma is a gamma function;
the classical Logistic equation is defined as:
in step (3), the computational generation of the chaotic signal comprises the following steps:
generating chaotic signals according to the selected parameters u (0), mu and v, and assigning values to the parameter n again;
inputting values of u (0), mu, v and n in formula (1), discarding the first 50 groups of signals, and drawing u (0), L, u (n) by a computer to generate chaotic signals u (0), L, u (n).
Further, the analog microwave receiver is provided with a signal energy detection module, and a signal detection method of the signal energy detection module comprises the following steps:
first, the method comprisesThe radio frequency or intermediate frequency sampling signal in the driven _ V1 or the driven _ V2 carries out NFFTFFT operation of point number, then modulus operation, and the first NFFTThe 2 points are stored in a vector F, the amplitude spectrum of a signal x2 is stored in the vector F, and x2 is a signal with zero intermediate frequency;
the second step is to divide the analysis bandwidth Bs into N equal blocks, where N is 3, 4, and]allocating frequency points of the corresponding frequency band in the vectorF to each block, wherein the range of vectorF points divided by nBlock is [ S ]n，Sn+kn]Wherein the number of frequency points divided per segment is shown, and Sn ═ round ((FL + (n-1) BsN)&CenterDot；NFFTfs)]]>The starting point is shown, fs is the signal sampling frequency, round (×) represents the rounding operation;
thirdly, solving the energy E | · of the frequency spectrum of each Block2Obtaining e (N), N ═ 1.. N;
fourthly, averaging the vector E;
fifthly, solving the sum of the variances of the vector E;
and sixthly, updating a flag bit flag, wherein the flag bit flag is 0 and indicates that the previous detection result is no signal, and only when sigma is in the conditionsum>When K2, judging that the signal is currently detected, and changing the flag to 1; when flag is 1, the previous detection result is a signal, and under the condition, only when sigma issum<When K1, the signal is judged not to be detected currently, the flag is changed to 0, K1 and K2 are threshold values, the threshold values are given by theoretical simulation matched with empirical values, and K2>K1；
And seventhly, controlling whether the subsequent demodulation threads and the like are started or not according to the flag bit: and if the flag is 1, starting the subsequent demodulation thread and the like, and otherwise, closing the subsequent demodulation thread.
The invention has the advantages and positive effects that: this intelligence microwave frequency channel radio monitoring control system through setting up the microwave transmitter to the microwave transmitter can change the frequency point at 100MHz within range, and the flexibility is strong, and sets up first helical antenna and second helical antenna and transmit and received signal, and the image that the microwave transmitter sent, accompanying sound modulation have adopted phase-locked loop technique, and the frequency stability is high, receives ambient temperature to influence for a short time.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent microwave frequency band radio monitoring control system according to the present invention.
In the figure: 1. a camera; 2. a microwave receiver; 3. a first helical antenna; 4. a second helical antenna; 5. simulating a microwave receiver; 6. a microwave transmitter; 7. a television or monitor.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, an intelligent microwave frequency band radio monitoring control system provided in an embodiment of the present invention includes:
the signals are transmitted to the camera 1 of the remote monitoring point microwave transmitter 6 through a video line.
The remote transmission can be carried out by transmitting 1 path of video signals and 1-2 paths of audio signals, and a corresponding number of microwave receivers 2 are arranged at a central point corresponding to each far-end point.
A first helical antenna 3 for transmitting signals of a microwave transmitter.
After the signal is transmitted to the amplifier, the signal is transmitted to a second spiral antenna 4 of the analog microwave receiver; .
And the analog microwave receiver 5 is used for receiving the video signal demodulated by the microwave signal transmitted by the second spiral antenna.
A television or monitor 7 connected directly to the analogue microwave receiver.
Furthermore, the modulation range of the microwave transmitter is +/-100 MHz;
furthermore, the television wall equipment is connected in a unified mode, and the hard disk video recorder is connected in a unified mode to record the video.
Furthermore, the frequency point of the microwave transmitter can be changed within the range of +/-100 MHz, and the flexibility is strong.
Furthermore, the image and sound transmitted by the microwave transmitter are modulated by adopting a phase-locked loop technology, so that the frequency stability is high, and the influence of the ambient temperature is small.
The structure of the present invention is further described below with reference to a control method of an intelligent microwave frequency band radio monitoring control system.
Firstly, a camera transmits signals to a microwave transmitter of a remote monitoring point through a video line;
secondly, the microwave transmitters can transmit 1 path of video signals and 1-2 paths of audio signals for remote transmission, corresponding to each far-end point, a corresponding number of microwave receivers are configured at the central point, and each microwave transmitter can wirelessly transmit the 1 path of video signals and the 1-2 paths of audio signals to complete point-to-point transmission of monitoring images;
then, the first spiral antenna transmits the signal of the microwave transmitter, and the signal is transmitted to the amplifier through the second spiral antenna and then transmitted to the analog microwave receiver;
and finally, the analog microwave receiver receives the microwave signal transmitted by the second spiral antenna, and then the demodulated video signal is directly connected to a television or a monitor, is uniformly connected to television wall equipment and is uniformly connected to a hard disk video recorder for recording.
The microwave transmitter can change frequency points within the range of +/-100 MHz and has strong flexibility.
The image and accompanying sound transmitted by the microwave transmitter are modulated by adopting a phase-locked loop technology, so that the frequency stability is high, and the influence of the environmental temperature is small.
Further, the camera is provided with an image transition module, and the salient rigid processing method of the image transition module comprises the following steps:
for any pixel x, calculating the certainty factor of the gray value g (x) of the pixel x to three cloud models Cl, Ct and Ch in a low gray area, a transition area and a high gray area, and recording the certainty factor as mul(x),μt(x),μh(x) (ii) a If and only if mut(x) When taking the maximum value, the pixel x is divided into the transition region, set to gTRDetermining a principle form for the transition region imageThe formula is shown as follows:
after the transition region pixel set is uncertainly obtained, the gray peak value of the pixel set is calculated and used as the optimal threshold value of the segmentation image.
Further, the image information pulse coupling neural network model of the camera is as follows:
Fij[n]＝Sij；
Uij[n]＝Fij[n](1+βij[n]Lij[n])；
θij[n]＝θ0e-αθ(n-1)；
wherein, betaij[n]Is an adaptive link strength coefficient;
Sij、Fij[n]、Lij[n]、Uij[n]、θij[n]respectively, input image signal, feedback input, link input, internal activity item and dynamic threshold, NwSelecting 1-3 for the total number of pixels in the selected window W to be processed and delta as an adjustment coefficient.
Further, the camera is provided with an image enhancement module, and an image enhancement method of the image enhancement module adopts a sparse redundancy model algorithm to enhance images;
firstly, an original image is polluted by additive Gaussian noise, the polluted image is called a degraded image, and the image recovery process is the reverse process of the degraded image; assume that the degradation model of the image is:
g＝Hu+v；
the restoration model of the image is then expressed as:
due to the interference of noise, a proper and unique solution cannot be obtained, and a regularization constraint is applied to the recovery model of the image; the restoration model of the image becomes a variational model:
r (u) is a regular term that is related to the nature of the image itself.
Further, the microwave receiver is provided with a chaotic sequence generating module, and the chaotic sequence generating method of the chaotic sequence generating module comprises the following steps:
(1) inputting system parameters:
obtaining a discrete function model:
in formula (1): u (0) is an initial signal, mu is a chaotic parameter, v is a fractional order, N is a signal length, j represents the iteration of the j step, alpha (mu, v, j, N) is a discrete integral kernel, u (N) is a signal of the N step, N and N are set to be 800, m is an integer of 1, L and N;
according to the formula (1), parameters u (0), mu and v are selected;
(2) judging whether the parameters can generate chaotic signals:
the tangent map b (m) is first calculated:
and then calculating the Lyapunov exponent lambda:
the same reference numerals in the formulas (2), (3) and (1) denote the same reference numerals;
the judgment basis is as follows: calculating lambda according to the formula (1), the formula (2) and the formula (3), if the lambda is greater than 0, the chaotic signal can be generated, otherwise, the chaotic signal cannot be generated;
(3) and calculating to generate chaotic signals.
Further, in step (1), the obtaining of the discrete function model includes:
by using a fractional discrete calculus method, a classical Logistic equation is modified into the following difference equation:
in the formula (4), the reaction mixture is,
a fractional order difference operator, wherein t is 1-v, 2-v, and a is an initial point;
taking a in the formula (4) as 0, and further converting the formula (4) into a discrete function model:
further, the function model of the fractional order discrete calculus is:
in the formula (4), a is an initial point, ν < 1 is a fractional order, t is a +1- ν, and a +2- ν, the first step is a fractional order,
gamma is a gamma function;
the classical Logistic equation is defined as:
in step (3), the computational generation of the chaotic signal comprises the following steps:
generating chaotic signals according to the selected parameters u (0), mu and v, and assigning values to the parameter n again;
inputting values of u (0), mu, v and n in formula (1), discarding the first 50 groups of signals, and drawing u (0), L, u (n) by a computer to generate chaotic signals u (0), L, u (n).
Further, the analog microwave receiver is provided with a signal energy detection module, and a signal detection method of the signal energy detection module comprises the following steps:
in the first step, the radio frequency or intermediate frequency sampling signal in the received _ V1 or received _ V2 is processed by NFFTFFT operation of point number, then modulus operation, and the first NFFTThe 2 points are stored in a vector F, the amplitude spectrum of a signal x2 is stored in the vector F, and x2 is a signal with zero intermediate frequency;
the second step is to divide the analysis bandwidth Bs into N equal blocks, where N is 3, 4, and]allocating frequency points of the corresponding frequency band in the vectorF to each block, wherein the range of vectorF points divided by nBlock is [ S ]n，Sn+kn]Wherein the number of frequency points divided per segment is shown, and Sn ═ round ((FL + (n-1) BsN)&CenterDot；NFFTfs)]]>The starting point is shown, fs is the signal sampling frequency, round (×) represents the rounding operation;
thirdly, solving the energy E | · of the frequency spectrum of each Block2Obtaining e (N), N ═ 1.. N;
fourthly, averaging the vector E;
fifthly, solving the sum of the variances of the vector E;
and sixthly, updating a flag bit flag, wherein the flag bit flag is 0 and indicates that the previous detection result is no signal, and only when sigma is in the conditionsum>When K2, judging that the signal is currently detected, and changing the flag to 1; when flag is 1, the previous detection result is a signal, and under the condition, only when sigma issum<When K1, the signal is judged not to be detected currently, the flag is changed to 0, K1 and K2 are threshold values, the threshold values are given by theoretical simulation matched with empirical values, and K2>K1；
And seventhly, controlling whether the subsequent demodulation threads and the like are started or not according to the flag bit: and if the flag is 1, starting the subsequent demodulation thread and the like, and otherwise, closing the subsequent demodulation thread.
The structure of the present invention will be further described with reference to the working principle.
According to the intelligent microwave frequency band radio monitoring control system, the microwave transmitter is arranged, the frequency point can be changed within the range of +/-100 MHz, the flexibility is high, the first spiral antenna and the second spiral antenna are arranged for transmitting and receiving signals, the phase-locked loop technology is adopted for modulating images and accompanying sounds sent by the microwave transmitter, the frequency stability is high, and the influence of the environmental temperature is small.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. An intelligent microwave frequency band radio monitoring control system, characterized in that, the intelligent microwave frequency band radio monitoring control system includes:
transmitting the signal to a camera of a remote monitoring point microwave transmitter through a video line;
the system can transmit 1 path of video signals and 1-2 paths of audio signals for remote transmission, and corresponding to each far-end point, a corresponding number of microwave receivers are configured at the central point;
a first helical antenna for transmitting signals of a microwave transmitter;
transmitting the signal to an amplifier and then to a second spiral antenna of the analog microwave receiver;
the analog microwave receiver is used for receiving the microwave signal transmitted by the second spiral antenna and demodulating a video signal;
a television or monitor directly connected to the analog microwave receiver;
the modulation range of the microwave transmitter is +/-100 MHz;
the television or the monitor is electrically connected with the television wall equipment or the hard disk video recorder;
the camera is provided with an image transition module, and the salient rigid processing method of the image transition module comprises the following steps:
for any pixel x, calculating the certainty factor of the gray value g (x) of the pixel x to three cloud models Cl, Ct and Ch in a low gray area, a transition area and a high gray area, and recording the certainty factor as mul(x),μt(x),μh(x) (ii) a If and only if mut(x) When taking the maximum value, the pixel x is divided into the transition region, set to gTRFor the transition region image, the determination principle is formalized as follows:
calculating the gray peak value of the pixel set after the transition region pixel set is uncertainly obtained, and taking the gray peak value as the optimal threshold value of the segmentation image;
the image information pulse coupling neural network model of the camera is as follows:
Fij[n]＝Sij；
Uij[n]＝Fij[n](1+βij[n]Lij[n])；
θij[n]＝θ0e-αθ(n-1)；
wherein, betaij[n]Is an adaptive link strength coefficient;
Sij、Fij[n]、Lij[n]、Uij[n]、θij[n]respectively, input image signal, feedback input, link input, internal activity item and dynamic threshold, NwSelecting 1-3 for the total number of pixels in the selected window W to be processed and delta as an adjustment coefficient.
2. The intelligent microwave frequency band radio monitoring control system according to claim 1, wherein the camera is provided with an image enhancement module, and an image enhancement method of the image enhancement module adopts a sparse redundancy model algorithm for image enhancement;
firstly, an original image is polluted by additive Gaussian noise, the polluted image is called a degraded image, and the image recovery process is the reverse process of the degraded image; assume that the degradation model of the image is:
g＝Hu+v；
the restoration model of the image is then expressed as:
due to the interference of noise, a proper and unique solution cannot be obtained, and a regularization constraint is applied to the recovery model of the image; the restoration model of the image becomes a variational model:
r (u) is a regular term that is related to the nature of the image itself.
3. The intelligent microwave frequency band radio monitoring control system according to claim 1, wherein the microwave receiver is provided with a chaotic sequence generating module, and a chaotic sequence generating method of the chaotic sequence generating module comprises:
(1) inputting system parameters:
obtaining a discrete function model:
in formula (1): u (0) is an initial signal, mu is a chaotic parameter, v is a fractional order, N is a signal length, j represents the iteration of the j step, alpha (mu, v, j, N) is a discrete integral kernel, u (N) is a signal of the N step, N and N are set to be 800, m is an integer of 1, L and N;
according to the formula (1), parameters u (0), mu and v are selected;
(2) judging whether the parameters can generate chaotic signals:
the tangent map b (m) is first calculated:
and then calculating the Lyapunov exponent lambda:
the same reference numerals in the formulas (2), (3) and (1) denote the same reference numerals;
the judgment basis is as follows: calculating lambda according to the formula (1), the formula (2) and the formula (3), if the lambda is greater than 0, the chaotic signal can be generated, otherwise, the chaotic signal cannot be generated;
(3) and calculating to generate chaotic signals.
4. The intelligent microwave band radio monitoring control system according to claim 3, wherein in step (1), the discrete function model obtaining comprises:
by using a fractional discrete calculus method, a classical Logistic equation is modified into the following difference equation:
in the formula (4), the reaction mixture is,
a fractional order difference operator, wherein t is 1-v, 2-v, and a is an initial point;
taking a in the formula (4) as 0, and further converting the formula (4) into a discrete function model:
5. the intelligent microwave band radio monitoring control system of claim 3 wherein the functional model of the fractional order discrete calculus is:
in formula (4), a is an initial point, ν < 1 is a fractional order, t is a +1- ν, a +2- ν, Δ u(s) u (s +1) -u(s),
gamma is a gamma function;
the classical Logistic equation is defined as:
in step (3), the computational generation of the chaotic signal comprises the following steps:
generating chaotic signals according to the selected parameters u (0), mu and v, and assigning values to the parameter n again;
inputting values of u (0), mu, v and n in formula (1), discarding the first 50 groups of signals, and drawing u (0), L, u (n) by a computer to generate chaotic signals u (0), L, u (n).
6. The intelligent microwave band radio monitoring control system according to claim 1, wherein the analog microwave receiver is provided with a signal energy detection module, and a signal detection method of the signal energy detection module comprises:
in the first step, the radio frequency or intermediate frequency sampling signal in the received _ V1 or received _ V2 is processed by NFFTFFT operation of point number, then modulus operation, and the first NFFTThe 2 points are stored in a vector F, the amplitude spectrum of a signal x2 is stored in the vector F, and x2 is a signal with zero intermediate frequency;
the second step is to divide the analysis bandwidth Bs into N equal blocks, where N is 3, 4, and]allocating frequency points of the corresponding frequency band in the vectorF to each block, wherein the range of vectorF points divided by nBlock is [ S ]n，Sn+kn]Wherein the number of frequency points divided per segment is shown, and Sn ═ round ((FL + (n-1) BsN)&CenterDot；NFFTfs)]]>The starting point is shown, fs is the signal sampling frequency, round (×) represents the rounding operation;
thirdly, solving the energy E | · of the frequency spectrum of each Block2Obtaining e (N), N ═ 1.. N;
fourthly, averaging the vector E;
fifthly, solving the sum of the variances of the vector E;
and sixthly, updating a flag bit flag, wherein the flag bit flag is 0 and indicates that the previous detection result is no signal, and only when sigma is in the conditionsum>When K2, judging that the signal is currently detected, and changing the flag to 1; when flag is 1, the previous detection result is a signal, and under the condition, only when sigma issum<When K1, the signal is judged not to be detected currently, the flag is changed to 0, K1 and K2 are threshold values, the threshold values are given by theoretical simulation matched with empirical values, and K2>K1；
And seventhly, controlling whether the subsequent demodulation thread is started or not according to the flag bit: and if the flag is 1, starting the subsequent demodulation thread, and otherwise, closing the subsequent demodulation thread.
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| CN103337699A (en) * | 2013-06-14 | 2013-10-02 | 西安希德电子信息技术有限公司 | First-generation Beidou microtrip and spiral navigation antenna |
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| CN102496153A (en) * | 2011-11-04 | 2012-06-13 | 西安电子科技大学 | SAR image speckle suppression method based on dictionary learning in wavelet domain |
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