CN114462458A - Ship underwater signal noise reduction and target enhancement method - Google Patents

Ship underwater signal noise reduction and target enhancement method Download PDF

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CN114462458A
CN114462458A CN202210370777.1A CN202210370777A CN114462458A CN 114462458 A CN114462458 A CN 114462458A CN 202210370777 A CN202210370777 A CN 202210370777A CN 114462458 A CN114462458 A CN 114462458A
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intrinsic mode
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姜莹
刘宗伟
杨春梅
吕连港
张远凌
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First Institute of Oceanography MNR
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Abstract

The invention relates to a method for reducing noise and enhancing a target of an underwater signal of a ship, belonging to the technical field of ocean information. The method has no influence of selection of parameters, threshold values and the like, does not need prior knowledge, has wide application range, can effectively reduce noise of underwater signals of ships and enhance target characteristics, and improves subsequent identification performance.

Description

Ship underwater signal noise reduction and target enhancement method
Technical Field
The invention belongs to the technical field of ocean information, and particularly relates to a ship underwater signal noise reduction and target enhancement method based on an intrinsic probability density function.
Background
Accurate identification of the marine vessel target has important practical significance on marine vessel monitoring, air route planning and marine equity maintenance. Currently, underwater radiated noise is one of the commonly used signals in ship identification.
Noise signals generated in the sailing process of ships can be transmitted to the periphery in the form of sound waves under water. The sound wave propagation can be influenced by the boundaries of the marine water body environment and the sea surface and the sea bottom, and is a complex physical process which is expressed in two aspects: one is that the acoustic channel will modulate the signal during propagation, resulting in energy loss and distortion of the signal; the other is that the physical ocean dynamic phenomena such as ocean, internal wave and frontal surface can introduce noise and cover useful signals. With the development of vibration and noise reduction technology and material science, the ship radiation noise becomes weaker and weaker, so that the ship radiation noise is difficult to be effectively and accurately identified from the ocean background noise.
At present, the acoustic identification of ships mainly depends on human ears to listen to underwater noise signals subjected to noise reduction and enhancement processing, and corresponding physical information of ships, such as types, propeller rotating speeds, blade numbers and the like, is judged manually according to intuition and experience. The effectiveness of the recognition depends mainly on the noise reduction and feature enhancement processing of the signal.
The main purpose of feature enhancement is to reduce noise components in the received signal as much as possible, enhance target components in the signal to improve data quality, and improve recognition performance. At present, researchers at home and abroad propose various methods for enhancing target signals, mainly including: filtering techniques, signal transformation techniques, and signal decomposition techniques. The filtering technology depends on the statistical characteristics of signals, can only process linear and stable signals, cannot cope with the condition that target signals and noise frequency bands are overlapped, and is not suitable for processing ship noise signals. The signal transformation technology mainly utilizes various transformation methods to localize signal time frequency to deal with the non-stationary characteristic of a target, but has the influence of selection of parameters, threshold values and the like, needs prior knowledge, and is limited in application range and enhancement performance. The signal decomposition technology mainly comprises Empirical Mode Decomposition (EMD) and an improved algorithm thereof and a Variational Mode Decomposition (VMD) algorithm, and also has the problems of dependence on prior information and limited application range and performance.
Disclosure of Invention
The invention aims to solve the technical problem of providing a ship underwater signal noise reduction and target enhancement method based on an intrinsic probability density function.
The invention solves the technical problem by the following technical scheme:
a ship underwater signal noise reduction and target enhancement method specifically comprises the following steps:
firstly, extracting a section of noise signal s with the total length T to obtain a normalized noise signal st(ii) a The step of normalizing is to unify the sampling rates of the different data samples to FSstdIn which FSstdGreater than 20 kHz; the dc component of the signal is then removed:
Figure 459698DEST_PATH_IMAGE001
where mean () represents the averaging operation; finally, normalizing the signal power:
Figure 970314DEST_PATH_IMAGE002
wherein std () represents a take standard deviation operation;
secondly, calculating an intrinsic mode function of the signal; first, for the signal stCarrying out modal decomposition, wherein the modal decomposition method comprises the following steps: after modal decomposition, it is expressed as:
Figure 218892DEST_PATH_IMAGE003
,
Figure 958309DEST_PATH_IMAGE004
（1）
wherein, ci(t) isiAn Intrinsic Mode Function (IMF) component;
further, for ship noise, N in equation (1) is greater than 8.
Thirdly, calculating a probability density function of the intrinsic mode function; for the first 8 intrinsic mode functions, the probability density function estimated by the kernel function is obtained
Figure 569419DEST_PATH_IMAGE005
；
Figure 470510DEST_PATH_IMAGE006
（2）
Where K () is a kernel function and h is a smoothing parameter.
Further, the kernel function in the formula (2) is a gaussian function corresponding to the normal distribution, then
Figure 65440DEST_PATH_IMAGE007
（3）
Fourthly, solving the deviation of the signal intrinsic probability density function and the Gaussian function; selecting an intrinsic mode function with the maximum deviation absolute value exceeding 0.04; when the number of the selected intrinsic mode functions is not more than 3, selecting 3 intrinsic mode functions with the largest deviation mean value;
and fifthly, adding the selected intrinsic mode functions in a time domain to finish the processing of ship underwater signal noise reduction and target enhancement.
Compared with the prior art, the invention has the beneficial effects that:
the method of the invention uses the deviation of the signal intrinsic probability density function and the Gaussian function to measure the target characteristics in the ship noise, and gets rid of the requirement on prior information; the deviation represents the condition of deviation from normal distribution in the signal, which often corresponds to the external force action of the physical structure (mainly driven by a propeller) of the ship on the water body, and can effectively obtain the target components. The method has no influence of selection of parameters, threshold values and the like, does not need prior knowledge, has wide application range, can effectively reduce noise of underwater signals of ships and warships and enhance target characteristics, and improves subsequent identification performance.
Drawings
FIG. 1 is a flow chart of the process steps of the method of the present invention;
FIG. 2 is a diagram of eigenmode functions obtained by decomposition of a ship signal;
FIG. 3 is a graph of a probability density function versus a Gaussian function for each eigenmode function;
fig. 4 is a comparison of the DEMON spectrum of the signal before and after the enhancement processing.
Detailed Description
The technical solution of the present invention is further explained by the following examples, but the scope of the present invention is not limited in any way by the examples.
Example 1
Taking the underwater noise signals of 1 ship as an example, the signals are divided into frames, the length of each frame is 10 seconds, and the frames are overlapped for 9 seconds. For each frame of data, the processing steps of the method of the invention (see fig. 1) are as follows:
and (5) standardizing operation in the first step. Performing normalization operation on a frame of noise signal s with the total length of 10 seconds to obtain a normalized noise signal st. Since the sampling rates are already consistent, uniform sampling rate operation is no longer required. Removing the direct current component of the signal:
Figure 467602DEST_PATH_IMAGE008
where mean () represents the averaging operation; power normalization of the signal:
Figure 540076DEST_PATH_IMAGE009
where std () represents a take standard deviation operation. After normalization, the time domain waveform of the signal is shown as Data in fig. 2.
In a second step, the eigenmode functions of the signal are calculated. First, for the signal stCarrying out modal decomposition, wherein the modal decomposition method comprises the following steps: empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), or adaptive noise-complete ensemble empirical mode decomposition (CEEM-EMD). Here, EEMD is selected to decompose these ship signals. After modal decomposition, the signal can be represented as:
Figure 346489DEST_PATH_IMAGE010
wherein c isi(t) is the Intrinsic Mode Function (IMF) component. As shown in FIG. 2, the result of signal decomposition is shown, wherein Data is the original signal, IMFiIs as followsiAnd each eigenmode function, namely Residual is decomposed, and the right-side numerical value is the frequency corresponding to each eigenmode function and the Residual.
And thirdly, calculating a probability density function of the intrinsic mode function. For each eigenmode function, the probability density function is obtained:
Figure 569660DEST_PATH_IMAGE011
where K () is a kernel function and h is a smoothing parameter. A gaussian function corresponding to a normal distribution is usually selected as a kernel function,
Figure 634568DEST_PATH_IMAGE012
h = 100. The probability density function for each eigenmode function is shown as a solid grey line in fig. 3.
And fourthly, solving the deviation of the signal intrinsic probability density function and the Gaussian function. And solving the deviation of the signal intrinsic probability density function and the Gaussian function. Selecting an intrinsic mode function with the maximum deviation absolute value exceeding 0.04; and when the number of the selected intrinsic mode functions is less than 3, selecting the 3 intrinsic mode functions with the largest deviation mean value. The probability density function (solid gray line) of each eigenmode function is compared to the gaussian function (dashed black line) as shown in fig. 3. From the results of fig. 3, it can be seen that the eigenmode functions selected for this signal are IMF2, IMF3, and IMF4, respectively.
And fifthly, overlapping the selected intrinsic mode functions on a time domain, and reconstructing the signals. The DEMON spectrum of the signal before and after the enhancement processing is shown in fig. 4, and the effect of the enhancement processing is very obvious. From the results of fig. 4, it can be seen that the peak position of the original signal DEMON spectrum is shown as a solid dot in the upper part of fig. 4, and is strongly deviated from the actual target (shown as a hollow dot); the peak position of the enhanced signal DEMON spectrum is shown as a hollow dot in the lower part of fig. 4, and does not deviate from the actual target.

Claims (3)

1. A ship underwater signal noise reduction and target enhancement method is characterized by specifically comprising the following steps:
firstly, extracting a section of noise signal s with the total length T to obtain a normalized noise signal st(ii) a The step of normalizing is to unify the sampling rates of the different data samples to FSstdIn which FSstdGreater than 20 kHz; the dc component of the signal is then removed:
Figure 857907DEST_PATH_IMAGE001
where mean () represents the averaging operation; finally, normalizing the signal power:
Figure 775047DEST_PATH_IMAGE002
wherein std () represents a take standard deviation operation;
secondly, calculating an intrinsic mode function of the signal; first, for the signal stCarrying out modal decomposition, wherein the modal decomposition method comprises the following steps: after modal decomposition, it is expressed as:
Figure 367833DEST_PATH_IMAGE003
,
Figure 763043DEST_PATH_IMAGE004
（1）
wherein, ci(t) isiAn intrinsic mode function component;
thirdly, calculating a probability density function of the intrinsic mode function; for the first 8 intrinsic mode functions, the probability density function estimated by the kernel function is obtained
Figure 639732DEST_PATH_IMAGE005
；
Figure 462194DEST_PATH_IMAGE006
（2）
Wherein, K () is a kernel function, and h is a smoothing parameter;
fourthly, solving the deviation of the signal intrinsic probability density function and the Gaussian function; selecting an intrinsic mode function with the maximum deviation absolute value exceeding 0.04; when the number of the intrinsic mode functions exceeding 0.04 is less than 3, selecting 3 with the largest deviation;
and fifthly, adding the selected intrinsic mode functions in a time domain to finish the processing of ship underwater signal noise reduction and target enhancement.
2. The method for reducing noise and enhancing target of underwater signal of ship as claimed in claim 1, wherein N in formula (1) is greater than 8 for ship noise.
3. The method of claim 1, wherein the kernel function in the formula (2) is a gaussian function corresponding to a normal distribution, and the method further comprises
Figure 542277DEST_PATH_IMAGE007
（3）。
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