CN109347580B - Self-adaptive threshold signal detection method with known duty ratio - Google Patents
Self-adaptive threshold signal detection method with known duty ratio Download PDFInfo
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Abstract
The invention relates to a self-adaptive threshold signal detection method with a known duty ratio. The method comprises the steps of firstly carrying out low-pass filtering smoothing on signal envelopes, then calculating the mean value and the second moment of the filtered signal envelopes, and reversely deducing the high level and the low level of a signal according to the mean value and the second moment, so that the optimal detection threshold of the signal is determined, the signal is detected, and meanwhile, the arrival time of the signal and the estimation of the signal duration can be determined. The method improves the weak signal detection probability of lower signal-to-noise ratio under the condition of a plurality of interference signals, and simultaneously reduces the false alarm probability; the method can be applied to the signal detection of the anti-unmanned aerial vehicle, and can also be applied to all other cooperative signal detection fields, such as the fields of communication multi-user detection, radar signal detection, cognitive radio and the like.
Description
Technical Field
The invention relates to the field of radio frequency spectrum sensing, in particular to a method capable of adaptively calculating a detection threshold and detecting under the condition of a known signal duty ratio in the field of anti-unmanned aerial vehicle radio frequency spectrum sensing.
Background
In recent years, various civil or industrial small and medium-sized unmanned aerial vehicles, especially small-sized multi-rotor unmanned aerial vehicles, not only become emerging professional equipment in various industries, but also become common hot tools in common people's life. But it also carries many security threats for low-altitude security. Because unmanned aerial vehicle is at the flight and the shooting in-process, need passback aircraft parameter and image data etc. so that the operator need control it, consequently unmanned aerial vehicle will send and observe and control and data transmission signal, the operator will also send remote control signal, and unmanned aerial vehicle of different producers, model observes and controls and data transmission signal has its respective parameter characteristics. The signals radiated by the unmanned aerial vehicles can be subjected to passive acquisition, parameter measurement and direction finding through a radio frequency spectrum sensing means, and the model of the unmanned aerial vehicle can be identified by judging the carrier frequency, the modulation mode, the duration and the like of the signals. And the unmanned aerial vehicle can be accurately positioned by measuring the direction of the unmanned aerial vehicle in a multi-station direction-finding crossing or time difference passive positioning mode, so that the unmanned aerial vehicle and an operator of the unmanned aerial vehicle can be positioned, identified and tracked possibly. Compared with various detection means such as radar, photoelectricity and sound detection, the radio frequency spectrum sensing means is widely concerned due to the characteristics that the detection distance is long, the influence of rain, snow, fog and illumination is avoided, the model recognition capability of the unmanned aerial vehicle is strong, and the like, and becomes an indispensable means in the field of anti-unmanned aerial vehicles.
In the anti-unmanned aerial vehicle radio frequency spectrum perception process, because the signal power of unmanned aerial vehicle transmission is very little, and the transmission frequency channel is mostly the public ISM frequency channel that need not to apply for moreover, probably has other stronger interference such as other signal interference sources such as Wifi data communication, bluetooth in the surrounding environment, how effective, reliably realize becoming a key problem to the detection of unmanned aerial vehicle signal under the low signal to noise ratio condition under the interference condition. Chinese patent 200910032873.X proposes a signal frequency spectrum sensing and detecting method based on decision threshold self-adaptation, at first separate out signal and noise on the basis of signal wavelet transform, estimate and calculate the decision threshold of the detector according to the noise power. Chinese patent 201110336915.6 proposes an adaptive threshold energy detection method, which dynamically adjusts the value of an energy decision threshold according to different signal-to-noise ratios by establishing an energy decision threshold decision function offline, and then performs decision online. The above method cannot adapt to the presence of multiple interfering signals or to dynamic adjustment of the receiver gain. Chinese patent 201110291275.1 proposes a method and apparatus for detecting cognitive radio spectrum based on adaptive dual thresholds, which selects a threshold value of this decision according to the result of the previous decision and the influence of random noise, and then decides the energy value E of the received signal based on the selected threshold value of this decision to obtain the result of this decision, but this method has poor effect of detecting weak signals. Chinese patent 201310344381.0 proposes a signal detection method based on energy detection, which determines whether there is a signal according to the energy variance of spectral segments in the system analysis bandwidth, but this method cannot determine the arrival time of the signal. Zhang Yulong, et al, proposed a signal detection algorithm based on statistical histogram (Zhang Yulong, a signal detection algorithm based on statistical histogram, military communication technology, 2017.3(1):26-30), dividing the signal into signal region, noise region and undetermined region on the basis of the mean filtering of the signal, the generation of histogram and the definition of noise and signal line, realizing the calculation and decision of adaptive threshold, the method has large calculation amount and weak detection effect on weak signal.
Since in the actual detection process, it is usually necessary to detect a plurality of (more than 3) types of specific drone signals, and the envelope of each type of drone signal has a relatively fixed duty cycle. Therefore, the duty ratio of the signal and the multi-moment characteristic of the signal can be utilized to determine the high level (signal plus noise amplitude) and the low level (noise amplitude) of the signal possibly existing in the interference, so as to optimally determine the better detection threshold.
Disclosure of Invention
The invention provides a signal self-adaptive detection method under the condition of a known duty ratio, aiming at the conditions of numerous interferences in the field of anti-unmanned aerial vehicles and low weak signal-to-noise ratio of signals to be detected. The method comprises the steps of firstly carrying out low-pass filtering smoothing on signal envelopes, then calculating the mean value (first moment) and the second moment of the filtered signal envelopes, and reversely deducing the high level and the low level of a signal according to the mean value and the second moment, so that the optimal detection threshold of the signal is determined, the signal is detected, and meanwhile, the arrival time of the signal and the estimation of the signal duration can be determined.
In order to achieve the above purpose, the invention firstly calculates envelope of the input signal x (t) and performs low-pass filtering, then calculates mean value and variance of the filtered signal envelope, and then calculates the optimal threshold to make decision. The method specifically comprises the following steps:
step 1: calculating envelope of input signal x (t) to obtain envelope signal x1(t) ═ x (t) |, where "| · |" denotes modulo arithmetic. The input signal can be a complex signal or a real signal;
step 2: for envelope signalx1(t) low-pass filtering to obtain filtered envelope signal x2(t) of (d). The bandwidth B of the low-pass filtering can be chosen to be the minimum possible duration τ of the desired detection signalmin8-10 times or more the reciprocal, but less than the bandwidth B of the input signal x (t)n(or receiver bandwidth), i.e.:
the specific low-pass filtering method can adopt all known filtering methods without influence.
And step 3: computing a filtered signal envelope x2The first order moment (mean) mu and the second order moment V of (t), i.e.
μ＝E(x2(t))
And 4, step 4: from a priori known signal average duty cycle
Wherein T is1For signal average duration, T0Calculating the high level V of the signal for the signal averaging intervalHAnd a low level VLI.e. by
Wherein a ═ T2q(1-q)+T2q2，b＝-2T2qμ，c＝T2μ2-T(1-q)V，T＝T1+T0Is the total duration of the signal;
and 5: calculating an optimal detection threshold of
In step 5, in order to ensure the robustness of calculation, when the method fails to calculate the optimal detection threshold (generally, when the signal duty ratio is assumed to be seriously deviated from the real condition), the average value is directly used for replacing the optimal detection threshold;
step 6: detecting the signal according to the optimal detection threshold, and enabling the rising edge to exceed the threshold ThIs defined as the signal arrival time ttoaWill fall below the threshold ThIs defined as the end time of the signal, and the signal duration τ can be determined by the signal arrival time and the end time.
The invention can achieve the following beneficial effects:
1. because the duty ratios of the useful signal and the interference signal are different, the method can improve the weak signal detection probability of lower signal-to-noise ratio under the condition of a plurality of interference signals and simultaneously reduce the false alarm probability;
2. the method can calculate the detection threshold in a self-adaptive manner, and can be suitable for the condition of unknown noise level of the receiver or the adjustment of gain change of the receiver;
3. the method of the invention can not only detect the existence of the signal, but also detect the signal arrival time and the signal duration, and can generate beneficial effects on signal type identification and time difference positioning;
4. the method can be applied to the signal detection of the anti-unmanned aerial vehicle, and can also be applied to all other cooperative signal detection fields, such as the fields of communication multi-user detection, radar signal detection, cognitive radio and the like.
Drawings
FIG. 1 is a schematic diagram of a signal detection method of the present invention;
FIG. 2 is a flow chart of a signal detection method according to the present invention;
fig. 3 is a waveform and result diagram of an embodiment of actual received signal detection.
Detailed Description
The invention is further described below with reference to the accompanying drawings and specific embodiments.
As shown in FIG. 1, the principle of the signal detection method of the present invention is that, because unknown noise is superimposed on the filtered envelope signal in the diagram, how to determine the amplitude V of the signal in the waveform containing noiseH(i.e., high level) and noise amplitude VL(low level) becomes an important issue. For this purpose, a statistical method may be used, i.e. the first and second moments mu, V of the signal are solved separately, and the first and second moments and the amplitude V of the signal are derivedH(i.e., high level) and noise amplitude VL(low level) there are the following relationships, respectively:
therefore, solving the above-mentioned binary quadratic equation, the values of the high level and the low level can be obtained:
wherein a ═ T2q(1-q)+T2q2，b＝-2T2qμ，c＝T2μ2-T(1-q)V，T＝T1+T0Is the total duration of the signal. The optimal threshold can be obtained according to the high level value and the low level value
As shown in fig. 2, the invention firstly calculates the envelope of the input signal x (t) and performs low-pass filtering, then calculates the mean and variance of the filtered signal envelope, and then calculates the optimal threshold for decision. The method specifically comprises the following steps:
step 1: calculating envelope of input signal x (t) to obtain envelope signal x1(t) ═ x (t) |, where "| · |" denotes modulo arithmetic. The input signal may be a complex signal or a real signal.
Step 2: for envelope signal x1(t) low-pass filtering to obtain filtered envelope signal x2(t) of (d). The bandwidth B of the low-pass filtering can be chosen to be the minimum possible duration τ of the desired detection signalmin8-10 times or more the reciprocal, but less than the bandwidth B of the input signal x (t)n(or receiver bandwidth).
And step 3: computing a filtered signal envelope x2The first order moment (mean) μ and the second order moment V of (t), i.e., μ ═ E (x)2(t))，
And 4, step 4: according to the known average duty ratio of the signal
Wherein T is1For signal average duration, T0For the signal average interval time, solving a binary quadratic equation, the high level V of the signal can be calculatedHAnd a low level VL。
And 5: calculating an optimal detection threshold of
In step 5, in order to ensure the robustness of the calculation, when the method fails to calculate (generally, mainly when the signal duty ratio is assumed to be seriously deviated from the real condition), the threshold is directly replaced by the average value.
Step 6: detecting the signal according to the optimal detection threshold, and enabling the rising edge to exceed the threshold ThIs defined as the signal arrival time ttoaWill fall below the threshold ThIs defined as the end time of the signal, has the signal arrival time and the end timeThe duration of the signal τ can be determined.
As shown in fig. 3, a receiving process diagram of the present invention for the waveform of the actual received signal is shown, and occasionally interference may occur due to both signal and noise in the actual signal. The signal amplitude has certain fluctuation, and then noise is superposed, so that the fluctuation is large. In order to enable reliable detection of the signal and accurate estimation of the duration, it is therefore critical how to find the optimal threshold. Therefore, by adopting the method of the invention, the estimated high level is 28.53, the estimated low level is 9.86, and the average of the two results in 19.19 as the optimal decision threshold. As can be seen from the figure, the decision threshold can better realize the decision on the presence or absence of the signal, and the arrival time and the duration of the signal are determined through the decision of the rising edge and the falling edge.
Claims (2)
1. A self-adaptive threshold signal detection method with known duty ratio comprises the steps of firstly carrying out low-pass filtering smoothing on signal envelopes, then calculating the mean value and the second moment of the filtered signal envelopes, and reversely deducing the high level and the low level of a signal according to the mean value and the second moment so as to determine the optimal detection threshold of the signal, realize the detection of the existence of the signal and simultaneously determine the arrival time of the signal and the estimation of the signal duration;
for an input signal x (t), firstly, calculating an envelope, performing low-pass filtering, then, calculating a mean value and a variance of the filtered signal envelope, and then, calculating an optimal threshold for judgment, specifically comprising the following steps:
step 1: calculating envelope of input signal x (t) to obtain envelope signal x1(t) ═ x (t) |, where "| · |" denotes modulo arithmetic, the input signal is a complex signal, or a real signal;
step 2: for envelope signal x1(t) low-pass filtering to obtain filtered envelope signal x2(t), the bandwidth B of the low-pass filtering can be chosen to be the minimum possible duration τ of the desired detection signalmin8-10 times or more the reciprocal, but less than the bandwidth B of the input signal x (t)nNamely:
the specific low-pass filtering method adopts a known filtering method;
and step 3: computing a filtered signal envelope x2The mean value μ and the second moment V of (t), i.e.
μ＝E(x2(t))
And 4, step 4: from a priori known signal average duty cycle
Wherein T is1For signal average duration, T0Calculating the high level V of the signal for the signal averaging intervalHAnd a low level VLI.e. by
Wherein a ═ T2q(1-q)+T2q2，b＝-2T2qμ，c＝T2μ2-T(1-q)V，T＝T1+T0Is the total duration of the signal;
and 5: calculating an optimal detection threshold of
Step 6: detecting the signal according to the optimal detection threshold, and enabling the rising edge to exceed the threshold ThIs defined as the signal arrival time ttoaWill fall below the threshold ThIs defined as the end time of the signal, and the signal duration τ can be determined by the signal arrival time and the end time.
2. The method according to claim 1, wherein in step 5, in order to ensure the robustness of the calculation, when the optimal detection threshold is not obtained, the average value is directly substituted for the optimal detection threshold.
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