CN110299926B - Underwater acoustic signal detection method oriented to low signal-to-noise ratio environment - Google Patents

Underwater acoustic signal detection method oriented to low signal-to-noise ratio environment Download PDF

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CN110299926B
CN110299926B CN201910675570.3A CN201910675570A CN110299926B CN 110299926 B CN110299926 B CN 110299926B CN 201910675570 A CN201910675570 A CN 201910675570A CN 110299926 B CN110299926 B CN 110299926B
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signal
variance
sequence
noise ratio
underwater acoustic
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CN110299926A (en
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张学武
朱晓坡
谢昱勃
徐晓龙
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Huixinjia Suzhou Intelligent Technology Co ltd
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Changzhou Campus of Hohai University
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Abstract

The invention discloses an underwater acoustic signal detection method oriented to a low signal-to-noise ratio environment, which comprises the following steps: setting the length of a transmitting signal, and processing a digital signal sequence to obtain an output sequence; processing the output sequence and calculating to obtain a sequence variance; comparing the sequence variance with a variance limit value to judge whether a signal exists or not; calculating the variance among all levels of elements in the output sequence and finding out the optimal threshold value; and obtaining the arrival time of the target signal according to the optimal threshold value, wherein the arrival time of the target signal is newly created for the complex water area environment, and the arrival time of the target signal comprises parts of normalized matched filtering, self-adaptive threshold value calculation, correlation peak extraction and the like. The signal detection performance of the received underwater sound signal under the low signal-to-noise ratio environment is improved by the normalized matched filtering and the self-adaptive threshold calculation of the received underwater sound signal.

Description

Underwater acoustic signal detection method oriented to low signal-to-noise ratio environment
Technical Field
The invention belongs to the field of underwater acoustic communication, and particularly relates to an underwater acoustic signal detection method oriented to a low signal-to-noise ratio environment
Background art:
in the application fields of underwater acoustic positioning, communication and the like, application requirements such as low power consumption, miniaturization and low cost are often faced due to the particularity of the application environment. Such requirements put higher requirements on the performance of a signal detection algorithm in the system in the aspect of low detection rate signal detection, and the system can be fully optimized in the aspects of power consumption, volume, cost and the like only if the system has the performance of accurately identifying and detecting pulses in the signal environment with low transmission power, low signal-to-noise ratio and low time-bandwidth product. Under the condition that the prior information such as impulse response and noise of the underwater acoustic channel is unknown, the most common signal detection scheme is a matched filter. The linear filter takes the maximum signal-to-noise ratio as a criterion, and has the characteristics of simple structure and convenient realization, so the linear filter is applied to a plurality of systems. Matched filters are also the most commonly used pulse signal detectors in underwater acoustic communication and positioning systems. However, the output signal of the time-varying hydroacoustic channel may exhibit a large dynamic range, and therefore the matched filter is typically normalized by a noise covariance matrix, which is commonly referred to as a Normalized Matched Filter (NMF).
Disclosure of Invention
The invention aims to provide an underwater acoustic signal detection method oriented to a low signal-to-noise ratio environment, which aims at the signal detection problem in underwater acoustic communication and communication systems and is oriented to the low signal-to-noise ratio acoustic environment, and improves the signal detection performance under the oriented application environment by the normalized matched filtering and the self-adaptive threshold judgment of received signals, thereby realizing the accurate estimation of the arrival time of target signals.
An underwater acoustic signal detection method oriented to a low signal-to-noise ratio environment comprises the following steps:
setting the length of a transmitting signal, and processing a digital signal sequence to obtain an output sequence;
processing the output sequence and calculating to obtain a sequence variance;
comparing the sequence variance with a variance limit value to judge whether a signal exists or not;
calculating the variance among all levels of elements in the output sequence and finding out the optimal threshold value;
and obtaining the arrival time of the target signal according to the optimal threshold value.
Preferably, the method for acquiring the output sequence includes the following steps:
setting the length N of a normalized matched filtering processing window as the length of a known transmitting signal s (t);
and performing sliding window processing on the digital signal sequence output by the underwater sound receiver in a normalized matched filtering mode to obtain a filtered output sequence.
Preferably, the processing method of the output sequence includes the following steps:
performing window skipping interception on the normalized matched filtering output sequence to obtain a filtering result, and calculating the variance according to the filtering result
Figure BDA0002143150970000021
Preferably, the method for determining the presence or absence of a signal includes the steps of:
variance is measured
Figure BDA0002143150970000023
And variance limit
Figure BDA0002143150970000024
Comparing;
if variance
Figure BDA0002143150970000025
Greater than the variance limit
Figure BDA0002143150970000026
There is a signal, otherwise there is no signal.
Preferably, the method for obtaining the optimal threshold value includes the following steps:
calculating the between-class variance of all elements within a window
Figure BDA0002143150970000022
Wherein 0<k<L, L is the resolution of the sequence sampling value;
finding out inter-class variance
Figure BDA0002143150970000036
Is the optimum threshold value k, i.e. k is
Figure BDA0002143150970000031
Preferably, the method for determining the arrival time of the target signal includes the following steps:
and finding out a part which is larger than the optimal threshold value in the cutoff window, wherein the position of the part in the sequence is the arrival time of the target signal.
Preferably, the normalized matched filter processing method includes:
the receiver signal is processed according to the following formula:
Figure BDA0002143150970000032
in the formula: s (t) is the original transmitted signal of the transmitter, y (t) is the underwater sound signal with noise and clutter received by the receiver, ykAnd skThe kth sample point in y (t) and s (t), respectively, ylFor filter coefficients, NMF denotes normalized matchingAnd a filter.
Preferably, the variance limit value
Figure BDA0002143150970000037
The value taking method comprises the following steps:
the calculation is carried out according to the set value of the false alarm rate when the detector is applied,
Figure BDA0002143150970000038
obeying a Gaussian distribution
Figure BDA0002143150970000033
From this, the false alarm rate estimation equation:
Figure BDA0002143150970000034
where erfc (·) is a complementary gaussian error function, i.e.:
Figure BDA0002143150970000035
thus calculate out
Figure BDA0002143150970000039
Wherein N is the window length,
Figure BDA00021431509700000310
the variance is represented and η represents the attenuation coefficient.
The invention has the advantages that: according to the underwater acoustic signal detection method oriented to the low signal-to-noise ratio environment, the signal detection performance under the aimed application environment is improved through the normalized matched filtering and the self-adaptive threshold judgment of the received signal, so that the accurate estimation of the target signal arrival time is realized, and the underwater acoustic signal detection performance under the low signal-to-noise ratio environment is far higher than that of other detection methods while the calculated amount is not greatly increased.
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FIG. 1 is a schematic diagram of a detector implementation structure of the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
As shown in fig. 1, a method for detecting underwater acoustic signals oriented to low signal-to-noise ratio environment includes the following steps:
(1) setting the length N of a normalized matched filtering processing window as the length of a known transmitting signal s (t), setting the length of a sliding window as 750 according to the product of the pulse width of a target signal and the conversion rate, and performing sliding window processing on a digital signal sequence output by the underwater acoustic receiver in a normalized matched filtering mode to obtain an output sequence;
(2) performing window skipping interception on the normalized matched filtering output sequence, wherein the window size is far larger than the length of the known transmitting signal s (t), and the window size is set to be 1.5 multiplied by 10 according to the product of the transmitting period and the conversion rate of the transmitter5；
(3) Calculating and acquiring the sequence variance in the cut window in the step (2)
Figure BDA0002143150970000041
(4) Judgment of
Figure BDA0002143150970000058
Whether or not it is greater than the variance limit
Figure BDA0002143150970000051
If not, determining that no target signal exists in the window, finishing the processing, and if so, continuing to perform the following steps;
(5) calculating the variance between classes of all elements in the window
Figure BDA0002143150970000052
Wherein 0<k<L, L is the resolution of the sequence sampling value;
(6) findingGo out
Figure BDA0002143150970000059
K is the optimum threshold value k, i.e. k is
Figure BDA0002143150970000053
(7) And finding out a part which is larger than k in the cut-off window, wherein the position of the part in the sequence is the arrival time of the target signal.
The normalized matched filtering process in step (1) processes the receiver signal according to formula (1),
Figure BDA0002143150970000054
where s (t) is the original transmitted signal of the transmitter, y (t) is the underwater sound signal with noise and clutter received by the receiver, ykAnd skThe kth sample point in y (t) and s (t), respectively.
Limiting value of square difference in step (4)
Figure BDA00021431509700000510
The value of (a) is calculated according to the set value of the false alarm rate when the detector is applied,
Figure BDA00021431509700000511
obeying a Gaussian distribution
Figure BDA0002143150970000055
From this to false alarm rate estimation
Figure BDA0002143150970000056
Where erfc (·) is a complementary Gaussian error function, i.e.
Figure BDA0002143150970000057
Thus calculate out
Figure BDA0002143150970000069
The value of (a).
Maximum between-class variance in step (5) and step (6)
Figure BDA0002143150970000061
The calculation of (1) is calculated according to an OTSU dynamic threshold method, and the specific calculation mode is as follows.
The size of a set of values is subdivided into L [1,2, …, L]Discrete sequence of levels, the number of samples of value i in the sequence being defined by niIndicating that the total number of sample points is N, N ═ N1+n2+…+nLThis histogram is normalized and then represented in the form of a probability distribution:
Figure BDA0002143150970000062
dividing the sequence into C by a threshold value k0And C1Two groups (background and target), C0The size of the sampling point is [1,2, …, k ]]In the set of (1), C1The sample point size is [ k +1, k +2, …, L]The probability of occurrence of these two classes and the average of the sampling points in these two classes are respectively
Figure BDA0002143150970000063
Figure BDA0002143150970000064
Figure BDA0002143150970000065
Figure BDA0002143150970000066
In the formula (I), the compound is shown in the specification,
Figure BDA0002143150970000067
is the first order integration instant of the kth level of the histogram. In addition to define
Figure BDA0002143150970000068
For the mean of the original signal, it is clear that for any k:
ω0μ0+ω1μ1＝μT,ω0+ω1＝1 (11)；
for the two classes of variances, respectively:
Figure BDA0002143150970000071
Figure BDA0002143150970000072
the definitions are introduced:
Figure BDA0002143150970000073
taking a threshold k corresponding to the maximum inter-class variance value as an optimal threshold value k for the inter-class variance, namely:
Figure BDA0002143150970000074
for an underwater acoustic positioning system, the invention calculates the direction and distance of the transponder by using the signal arrival time difference among array elements of a system matrix, so accurate time delay estimation is the basis for realizing the system function. The transponder transmits a chirp signal with a pulse time width of 5ms and a bandwidth [20kHz,28kHz ] with 1s as a signal transmission period. Each array element of the array is an underwater acoustic transducer, receives a transponder signal in real time, converts the underwater acoustic signal into an electric signal, outputs the electric signal to an analog-to-digital converter after passing through an analog signal conditioning circuit, has the conversion rate of 150ksps, and packages and uploads the electric signal to a system ground station for position resolution after being converted into a digital signal.
It will be appreciated by those skilled in the art that the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiments disclosed above are therefore to be considered in all respects as illustrative and not restrictive. All changes which come within the scope of or equivalence to the invention are intended to be embraced therein.

Claims (8)

1. An underwater acoustic signal detection method oriented to a low signal-to-noise ratio environment is characterized by comprising the following steps:
setting the length of a transmitting signal, and processing a digital signal sequence to obtain an output sequence;
processing the output sequence and calculating to obtain a sequence variance;
comparing the sequence variance with a variance limit value to judge whether a signal exists or not;
calculating the variance among all levels of elements in the output sequence and finding out the optimal threshold value;
and obtaining the arrival time of the target signal according to the optimal threshold value.
2. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 1, characterized in that: the method for acquiring the output sequence comprises the following steps:
setting the length N of a normalized matched filtering processing window as the length of a known transmitting signal s (t);
and performing sliding window processing on the digital signal sequence output by the underwater sound receiver in a normalized matched filtering mode to obtain a filtered output sequence.
3. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 2, characterized in that: the processing method of the output sequence comprises the following steps:
performing window skipping interception on the normalized matched filtering output sequence to obtain a filtering result, and calculating the variance according to the filtering result
Figure FDA0002752588810000011
4. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 1, characterized in that: the method for judging whether the signal exists or not comprises the following steps:
variance is measured
Figure FDA0002752588810000012
And variance limit
Figure FDA0002752588810000013
Comparing;
if variance
Figure FDA0002752588810000014
Greater than the variance limit
Figure FDA0002752588810000015
There is a signal, otherwise there is no signal.
5. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 1, characterized in that: the method for acquiring the optimal threshold value comprises the following steps:
calculating the between-class variance of all elements within a window
Figure FDA0002752588810000022
Wherein 0<k<L, L is the resolution of the sequence sampling value;
finding out inter-class variance
Figure FDA0002752588810000023
Is the optimum threshold value k, i.e. k is
Figure FDA0002752588810000024
6. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 1, characterized in that: the method for judging the arrival time of the target signal comprises the following steps:
and finding out a part which is larger than the optimal threshold value in the cutoff window, wherein the position of the part in the sequence is the arrival time of the target signal.
7. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 2, characterized in that: the method for performing sliding window processing on the digital signal sequence output by the underwater acoustic receiver in the form of normalized matched filtering comprises the following steps:
the receiver signal is processed according to the following formula:
Figure FDA0002752588810000021
in the formula: s (t) is the original transmitted signal of the transmitter, y (t) is the underwater sound signal with noise and clutter received by the receiver, ykAnd skThe kth sample point in y (t) and s (t), respectively, ylFor filter coefficients, NMF denotes a normalized matched filter.
8. The underwater acoustic signal detection method oriented to the environment with low signal-to-noise ratio according to claim 4, wherein: the variance limit value
Figure FDA0002752588810000025
The value taking method comprises the following steps:
the calculation is carried out according to the set value of the false alarm rate when the detector is applied,
Figure FDA0002752588810000026
obeying a Gaussian distribution
Figure FDA0002752588810000031
From this, the false alarm rate estimation equation:
Figure FDA0002752588810000032
where erfc (·) is a complementary gaussian error function, i.e.:
Figure FDA0002752588810000033
thus calculate out
Figure FDA0002752588810000034
Wherein N is the window length,
Figure FDA0002752588810000035
the variance is represented and η represents the attenuation coefficient.
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CN109507675A (en) * 2019-01-07 2019-03-22 中国科学院声学研究所东海研究站 The method for realizing the estimation processing of underwater multi-target time delay based on frequency division systems

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