KR102265899B1 - Method and apparatus for demon processing in order that removal of external target noise when measuring underwater radiated noise, computer-readable storage medium and computer program for controlling the holder device - Google Patents

Abstract

The present invention relates to a signal processing method and apparatus, a computer-readable recording medium, and a computer program capable of removing external target noise when measuring radiated noise in water. The method comprises the steps of: converting underwater radiated noise data into digital signals; performing windowing according to the distribution between a plurality of hydroacoustic listeners; converting a time domain signal into a frequency domain signal; normalizing to remove a magnitude term of a desired target signal; and extracting propulsion system information of an external target. According to the present invention, since signal processing is simple, configuration can be ensured at a low cost.

Description

Signal processing method and device, computer readable recording medium, and computer program capable of removing external target noise when measuring underwater radiated noise MEDIUM AND COMPUTER PROGRAM FOR CONTROLLING THE HOLDER DEVICE}

The embodiment relates to an underwater radiation noise signal processing technology, and more specifically, a signal processing method capable of removing and suppressing external target noise using GPS information and restoring and detecting the thruster noise (portion signal) of a desired target; and It's about the device.

If the propeller cavitation radiation noise signal generated from a ship or a high-speed underwater maneuvering target is processed by a DEMON signal, information such as the number of propeller shaft rotations, wing rotations and shaft numbers of the ship can be identified and distinguished.

In conventional DEMON signal processing, a signal received by a hydrophone is generally converted to a digital signal according to a predetermined sampling rate while passing through an A/D (Analog to Digital) processor. After that, the signal is subjected to a bandpass filter to reject direct current (DC) bias and high ambient noise in the low frequency band.

The signal that has passed through the bandpass filter is converted into a signal having an instantaneous intensity and an instantaneous phase value by converting a signal having a real value to a complex number through a Hilbert transform. Then, by calculating a root mean square (RMS) value from this value, it is converted into a value representing the size of the entire envelope of the measurement signal. Finally, by having a Fast Fourier Transform (FFT) process, it is possible to know the characteristics of a signal that appears periodically over a wide band, such as cavitation noise of a propeller.

However, there is an increasing demand for quantitative test evaluation of underwater radiation noise analysis of targets. However, if there are targets other than the measurement target during test evaluation and DEMON signal processing is performed using the prior art, unwanted external target noise information will appear at the same time. Such external target noise information introduces ambiguity in signal analysis. Therefore, it is necessary to separate the signal for radiated noise other than the desired target to enable objective and precise test evaluation support.

As a precedent document showing such target detection technology, the Journal of the Korean Acoustic Society, Vol. 36, No. 6 pp. 378~386 (a technique for improving underwater target distance estimation performance using blind deconvolution and time of arrival techniques), Korean Patent Registration No. 10-2015-0016745 (Title of the invention: Real-time sound source separation device compensating for phase distortion) , Korea Patent Registration No. 10-1303192 (Title of the invention: passive sonar system and its daemon processing improvement technique), and the like.

In the case of the method for improving the underwater target distance estimation performance using the double thesis blind deconvolution and time of arrival techniques, when the transmission signal is distorted by the multipath during underwater tracking in a multipath environment, the interference signal is removed and then the accurate transmission signal is restored. It relates to a method for improving underwater tracking accuracy. In particular, it is assumed that the received signal is a plane wave, and the direction of the direct path of the transmitted signal is estimated using a vertical line array system and delay and sum beamforming. It is a method of calculating the channel transfer function and removing the multipath signal by applying the blind deconvolution technique.

The method of improving the underwater target distance estimation performance using the blind deconvolution and time of arrival techniques described above and the present invention have a common feature of the present invention by applying a sound-based blind deconvolution method in an interference environment of multiple signals to obtain a channel transfer function. It calculates and removes the interference signal through the time reversal method. However, the present invention introduces the concept of focused beamforming without using the conventional plane wave assumption and vertical line array for calculating the channel transfer function after estimating the distance and azimuth values of the desired target to assume the curved wave. And to calculate the noise source level when measuring the underwater radiation noise, the relative distance and orientation were calculated using the measuring equipment and the Global Positioning System (GPS) installed on the desired target. Therefore, there is no need for multiple listeners for target detection, hardware and signal processing are relatively simple, and curved wave correction generated when a desired target passes close to the measuring device is possible, thereby improving the performance of the present invention. In addition, this method differs in the method of removing the DEMON signal of relatively low frequency external targets by applying the near-field sound-based blind deconvolution technique, rather than restoring the original signal after removing the multipath signal.

And in the case of Korean Patent Registration No. 10-2015-0016745, when a desired signal and noise are mixed and input, each signal is assumed to be mutually independent and blind deconvolution is based on an information maximization approach. deconvolution) to remove external noise.

A common feature between the Korea Patent Registration No. 10-2015-0016745 and the present invention is a method of detecting a desired target signal when noise is present. However, the present invention does not assume that each signal is independent of each other, and does not remove noise in a probabilistic manner, but uses a global positioning system (GPS)-based near-field sound-based blind deconvolution to spatially multiple There is a difference in removing the signal of the targets and restoring the desired target signal.

On the other hand, in the case of Korean Patent Registration No. 10-1303192, it is about a DEMON processing improvement technique using a sonar system, and the DEMON signal frequency effect on the radiated noise collected by the sensor can be removed. ) processing technique. A common feature between the Korea Patent Registration No. 10-1303192 and the present invention is that it relates to a DEMON processing improvement technique.

However, the present invention does not simply remove the tonal signal frequency effect, but spatially suppresses and removes the effect of all external noise to restore the spectrum energy for the desired target signal and RMS (Root Mean Sqaure) By going through the process, information such as the number of rotations of the propeller shaft and the number of blades and shafts of the desired target can be identified and distinguished.

The above prior art attempts to solve the difficulty of measuring target signal analysis due to the inflow of external target noise when measuring underwater acoustics. Therefore, according to Class B of the underwater radiation noise measurement guideline ANSI/ASA (AMERICAN NATIONAL STANDARD) S12.64-2009/PART 1, a Global Positioning System (GPS), at least three hydrophones, and a near-field sound-based blind decon By applying the blind deconvolution technique to separate the thruster noise of external targets, the target thruster signal to be measured can be analyzed more clearly.

In order to solve the above problems, the embodiment uses a global positioning system (GPS), a plurality of hydrophones, and a near-field sound-based blind deconvolution technique to separate the fraction signal of an external target and a desired target, and It is an object of the present invention to provide a signal processing method and apparatus capable of / or xkaq.

A signal processing method according to an embodiment includes converting underwater radiation noise data measured from a desired target and a plurality of external targets into a digital signal using a plurality of hydroacoustic listeners, and a cavitation frequency generation band in the radiation noise digital signal Applying a band-pass filter and performing windowing according to a distribution among the plurality of hydroacoustic devices, and converting a time domain signal received by the hydroacoustic listener into a frequency domain signal, including in the frequency domain signal Normalizing to remove the magnitude term of the desired target signal, and calculating the desired inclination distance and orientation between the targets from the hydroacoustic hearing device using a global positioning system (GPS) in the normalized signal; Calculating a phase correction factor, which is a weight vector, by substituting information on the inclination distance and azimuth function between targets to the concept of focused beamforming, and calculating the weight vector on the normalized signal to include the external target noise Calculating a transfer function, applying a blind deconvolution concept to apply a time reversal technique between the channel transfer function and the received target frequency domain signal to remove the external target noise and reconstructing a spectrum; performing reverse fast Fourier transform of the reconstructed spectrum into the time domain signal; calculating an RMS value on the result of the time domain signal; and using a fast Fourier transform on the RMS value to the external target It may include the step of extracting the propulsion system information of.

In addition, the signal processing apparatus according to the embodiment includes an A/D converter for converting underwater radiation noise data measured from a desired target and a plurality of external targets into a digital signal using a plurality of underwater acoustic listeners, and the radiation noise digital signal. Bandpass filter and frequency conversion for applying a bandpass filter that is a band of cavitation frequency generation, performing windowing according to distribution among the plurality of hydroacoustic devices, and converting a time domain signal received by the hydroacoustic listener into a frequency domain signal and a normalization unit for removing a magnitude term of the desired target signal included in the frequency domain signal, and a desired inclination distance between the targets from the hydroacoustic hearing device by using a global positioning system (GPS) in the normalized signal, and A target tracking unit that calculates an orientation, a phase correction factor calculator that calculates a phase correction factor that is a weight vector by substituting information on a tilt distance and an orientation function between targets in a focused beamforming concept; A channel transfer function estimator for calculating the channel transfer function including the external target noise by calculating the weight vector, and a blind deconvolution concept applied to the channel transfer function and the received target frequency domain signal By applying the time reversal method between a target signal restoration unit that removes the external target noise and restores a spectrum of a desired target signal, reverse fast Fourier transforms the restored spectrum into the time-domain signal, calculates an rms value on the time-domain signal result, and the rms value may include a signal calculation unit for extracting the propulsion system information of the external target by using the fast Fourier transform.

The embodiment can solve the difficulty of measuring target signal analysis due to the inflow of external target noise during underwater acoustic measurement, and it uses the existing underwater radiation noise measurement hardware without building additional equipment, and it is simple to process the signal, so it is low cost. It has a configurable effect.

In addition, the embodiment has an effect that can be usefully used in a place where it is difficult to have an ocean experiment without the inflow of noise from an external target during underwater acoustic measurement, such as in the Korean waters.

1 is a flowchart illustrating a signal processing method capable of removing external target noise when measuring underwater radiated noise according to an embodiment.
FIG. 2 is a simulation result graph when the signal processing process according to FIG. 1 is applied.
3 is a block diagram illustrating a signal processing device capable of removing external target noise when measuring underwater radiated noise according to an embodiment.

Since the present invention is capable of making various changes and dealing with various embodiments, specific embodiments are illustrated in the drawings and specifically described in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

In describing each figure, like reference numerals are used for like elements.

The terms first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. shouldn't

Hereinafter, a signal processing method and apparatus capable of removing external target noise when measuring underwater radiation noise according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart illustrating a signal processing method capable of removing external target noise when measuring radiated noise underwater according to an embodiment, and FIG. 2 is a simulation result graph when the signal processing process according to FIG. 1 is applied.

Referring to FIG. 1 , the signal processing method according to the embodiment comprises the steps of: A/D (Analog to Digital) conversion of radiated noise data measured from a hydrophone to remove an external target shaft rotation component to generate a noise digital signal can be performed (S100). Here, the step may convert underwater radiation noise data measured from a desired target and a plurality of external targets into digital signals using three or more hydroacoustic listeners .

Next, in order to remove the machinery noise of the targets and obtain envelope data of the shaft rotation component, the 1/1 octave band filter bank method 2kHz~4kHz, 4kHz within the cavitation frequency band of 3~10 kHz to the radiated noise digital signal Filtering can be performed in ~8kHz, 8kHz~10kHz bands. Then, in order to reduce the side lobes of the signal and collect the signal of the desired band, a hanning window according to the distribution between the hydroacoustic listeners may be performed (step S101).

Next, to reduce the amount of calculation and for convenience of signal processing, a step of converting the time-domain signal received by the hydrophone to a frequency-domain signal by using a Fast Fourier Transform (FFT) may be performed (step S102).

[Equation 1]

는 청음기 배열단 j번째 수신기 위치로 수신되는 시간영역 신호

가 주파수 영역으로 변산된 결과 값이고

는 원하는 표적의 위치

로부터 수신 청음기 배열단

번째 수신기 위치

에서의 채널 전달함수를 나타내며,

는 원하는 표적 신호의 크기 항,

는 원하는 표적 신호의 위상 항을 나타낸다. 다음으로 주파수 변환된 수신 신호에 원하는 표적 신호의 크기 항 제거를 위해 정규화시키는 단계를 수행할 수 있다(단계 S103).here,

is the time domain signal received at the j-th receiver position of the listener array.

is the result value transformed into the frequency domain,

is the desired target position

Listener array group receiving from

second receiver position

represents the channel transfer function in

is the magnitude term of the desired target signal,

denotes the phase term of the desired target signal. Next, a step of normalizing the frequency-converted received signal to remove the magnitude term of the desired target signal may be performed (step S103).

[Equation 2]

는 수신신호

에서 원하는 표적 신호의 크기 항

를 제거하기 위해 정규화한 결과이다. 정규화 과정을 거치면, 외부 표적 소음 및 시간지연 함수가 포함된 전달함수

와 원하는 표적 신호의 위상 항

만 분자 항에 남게 되고 크기 감쇄 노이즈로

가 분모 항에 남게 된다.here,

is the received signal

The magnitude term of the desired target signal in

The result is normalized to remove . After the normalization process, the transfer function including the external target noise and time delay function

and the phase term of the desired target signal

Only the numerator term is left and the size decay noise

remains in the denominator term.

Next, a step of tracking a desired target position using GPS may be performed (S104).

In other words, in order to remove the phase term value of the signal remaining in the normalized signal and to estimate only the channel transfer function, the spatial position of the desired target must be identified. The slope distance and bearing of the period can be calculated. In order to calculate the inclination distance, the horizontal distance between the measuring equipment and the desired target, depth information of the listeners, and azimuth information are required.

[Equation 3]

Here, WSSRc is an abbreviation of Wanted Ship Slant Range, and is the inclination distance between the middle sensor and the target among three or more desired measurement sensors, GPSR is the horizontal distance between the desired target and measuring equipment calculated by the satellite navigation system, and Sensor _c is 3 It means the middle sensor depth among the above measurement sensors. In addition, since WSSRc includes both target inclination distance and azimuth information, it is possible to calculate the time delay of a curved wave based on a focused beamforming concept (technique).

를 계산하는 단계를 수행할 수 있다(단계 S105).Next, the phase correction factor using the inclination distance and bearing information between the target and the measuring equipment

may be performed (step S105).

[Equation 4]

는 표적과 측정 장비간의 경사거리 및 방위 정보가 포함된 가중치 벡터를 의미하고 수신 신호와 정규화 신호와의 연산 후 angular 값을 취하면, 원하는 표적의 신호의 위상 항

및 원하는 표적과 청음기들 사이에 전송된 음파의 음선이동시간을 뜻하는 임의의 위상편이 항

이 도출된다. 이때, 가중치 벡터 쩌에 수학식 3에서 계산된 표적과 측정 장비간의 경사 거리 및 방위를 아래 식에 대입한다.here,

is a weight vector containing the inclination distance and azimuth information between the target and the measuring equipment, and if the angular value is taken after the operation of the received signal and the normalized signal

and an arbitrary phase shift term that means the sound line transit time of a sound wave transmitted between the desired target and the listeners.

this is derived At this time, the inclination distance and the orientation between the target and the measuring equipment calculated in Equation 3 in the weight vector ze are substituted into the following equations.

[Equation 5]

는 표적과 측정 센서로부터의 거리에 의해 변화되는 시간지연값을 뜻하며,

은 중간 센서로부터 위쪽에 설치된 센서로 수신되는 표적 신호의 지연시간,

는 중간 센서로부터 아래쪽에 설치된 센서로 수신되는 표적 신호의 지연시간을 뜻한다.where c is the average speed of sound in the water at the middle ear depth

is the time delay value that is changed by the distance from the target and the measuring sensor,

is the delay time of the target signal received from the middle sensor to the sensor installed above,

is the delay time of the target signal received from the middle sensor to the sensor installed below.

[Equation 6]

는 삼각함수를 이용하면 간단히 유도되며 수학식 3에서 계산된 표적과 측정 장비간의 경사거리(WSSRc) 및 방위 정보를 대입하면 센서에 따른 곡면파 시간지연을 계산할 수 있다. 위 가중치 벡터 Wj를 이용하여 위상보정인자를 계산하면 아래식과 같다.Here, the time delay function

is simply derived using a trigonometric function, and by substituting the slope distance (WSSRc) and azimuth information between the target and the measuring device calculated in Equation 3, it is possible to calculate the surface wave time delay according to the sensor. If the phase correction factor is calculated using the above weight vector Wj, it is as follows.

[Equation 7]

항은 선형위상 특성을 가지며 표적과 측정 장비간의 경사거리(WSSRc)로 인해 발생하는 시간지연 값과 등가이다. 그리고 가중치 벡터 Wj와 수신신호의 연산으로 인하여 표적 소음은 센서 개수만큼 증폭되고 외부 소음은 감소되어 표적 신호의 위상 항에 유사한

이 계산 가능하다.here,

The term has a linear phase characteristic and is equivalent to the time delay caused by the slope distance (WSSRc) between the target and the measuring device. And due to the calculation of the weight vector Wj and the received signal, the target noise is amplified by the number of sensors and the external noise is reduced so that the target signal is similar to the phase term

This can be calculated

와 위상보정인자

를 연산하여 표적 신호의 소음은 제거되고 외부 소음만이 포함된 채널 전달함수를 계산하는 단계를 수행할 수 있다(단계 S106).Next, the previously calculated normalized signal

and phase correction factor

, the noise of the target signal is removed and a step of calculating a channel transfer function including only external noise may be performed (step S106).

[Equation 8]

는 추정된 전달함수를 나타낸다.here,

is the estimated transfer function.

와 전달함수

를 디컨볼루션 하여 신호 스펙트럼을 계산하는 단계를 수행할 수 있다(단계 S107).Next, remove and suppress external target noise in the received signal and calculate the desired target signal spectrum.

and transfer function

A step of calculating a signal spectrum by deconvolution may be performed (step S107).

[Equation 9]

는 외부 표적 소음 및 시간지연 함수가 포함된 전달함수

가 제거 되었으며, 표적과 측정 장비간의 경사거리(WSSRc)로 인해 발생하는 시간지연 값

항과 크기 감쇄 노이즈로

항이 포함된 형태로 원 신호

항이 복원된 값이다.here,

is the transfer function including the external target noise and time delay function

has been removed, and the time delay value caused by the inclination distance (WSSRc) between the target and the measuring device

with term and magnitude decay noise

The raw signal in the form with terms

The term is the restored value.

의 포락선(Envelope) 계산을 위해 주파수 영역 신호를 시간 영역 신호로 역방향 고속 푸리에 변환(IFFT: Inverse Fast Fourier Transform)하여

를 계산하며

는 디지털 신호이다(단계S108).Next estimated target signal

Inverse Fast Fourier Transform (IFFT: Inverse Fast Fourier Transform) from a frequency domain signal to a time domain signal to calculate the envelope of

to calculate

is a digital signal (step S108).

에 실효치(RMS: Root Means Square)를 산출하는 단계를 수행할 수 있다(단계 S109).Next, the estimated target signal to obtain the desired target envelope size

A step of calculating a root mean square (RMS) may be performed (step S109).

[Equation 10]

횟수만큼 표적 신호

의 실효치(RMS: Root Means Square) 값을 계산하며, N은 다운 셈플링(down sampling)을 뜻하고 해상도를 고려하여 최대 0.05초를 넘지 않는다.where Z(D) is

target signal as many times as

Calculates the Root Means Square (RMS) value, where N means down sampling and does not exceed 0.05 seconds at most in consideration of resolution.

Next, a step of extracting propulsion system information (side propulsion system signal) after performing Fast Fourier Transform (FFT) on the result of Equation 10 to calculate the DEMON signal of the desired target. can be (step S110).

Referring to FIG. 2 , a first graph 201 is a result of performing a Fast Fourier Transform (FFT) on noise of a desired target and an external target and expressed as a spectrum. And the second graph 202 is the result of adding the noise of the desired target and the external target shown in the first graph 201 . The third graph 203 is the result of performing the conventional DEMON signal processing on the desired target signal of the first graph 201 in the 3 to 10 kHz band, and the number of propeller shaft rotations in the vicinity of about 1.7 Hz and 7.0 Hz information can be checked. The fourth graph 204 is the result of performing the conventional DEMON signal processing for the unwanted external target signal of the first graph 201 in the 3 to 10 kHz band, and the propeller shaft rotation number is around 3.6 Hz. information can be checked.

The 5th, 6th, and 7th graphs 205, 206, and 207 are 1/1 octave band filter bank method 2~4 kHz, 4~ with respect to the combined signal of the second graph 202 with the existing DEMON technique. This is the result of signal processing in the 8 kHz and 8-10 kHz bands, and in particular, in the 6th and 7th graphs (206, 207) where the signals were processed in the 4-8 kHz and 8-10 kHz bands, the About 3.6 Hz component, which is information, can be confirmed.

On the other hand, the results of signal processing in the bands of 2-4 kHz, 4-8 kHz, and 8-10 kHz for the combined signal of the second graph 202 by the proposed DEMON technique are shown in the 8th, 9th, and 10th graphs. It is the same as (208, 209, 210), and it can be confirmed that the about 3.6 Hz component, which is information of the external target propeller shaft rotation speed, is removed.

3 is a block diagram illustrating a signal processing device capable of removing external target noise when measuring underwater radiated noise according to an embodiment.

Referring to FIG. 3 , the signal processing device 300 measures the first to nth targets 301-1 to 301-n to generate radiation noise measurement data 1st to nth underwater acoustic listeners 310-1 to 310-n), a signal processing unit 320 that processes radiated noise measurement data to calculate a DEMON signal, a position tracking unit that calculates a phase correction factor using a global positioning system (GPS) ( 330), etc.

The signal processing unit 320 may include an A/D converter 321 . The A/D converter 321 may convert underwater radiation noise data measured from a desired target and a plurality of external targets into a digital signal using a plurality of hydroacoustic listeners.

The signal processor 320 may include a bandpass filter and a frequency converter 322 .

The band-pass filter and frequency converter 322 applies a band-pass filter that is a cavitation frequency generation band to the radiated noise digital signal, performs windowing according to the distribution among the plurality of hydroacoustic listeners, and is received by the hydroacoustic listener A time domain signal can be converted into a frequency domain signal.

The signal processing unit 320 may include a normalization unit 323 .

The normalizer 323 may remove a magnitude term of a desired target signal from the received data.

The signal processing unit 320 may include a transfer function estimating unit 324 .

The transfer function estimator 324 may remove the phase term of the desired target signal remaining in the normalized data.

The signal processing unit 320 may include a target signal restoration unit 325 .

The target signal restoration unit 325 may remove an external target noise from the received signal using a channel transfer function.

The signal processing unit 320 may include a signal calculating unit 326 .

The signal calculator 326 reversely converts the reconstructed spectrum into the time-domain signal, calculates an effective value on the time-domain signal result, and uses the fast Fourier transform on the effective value to provide propulsion system information of the external target. can be extracted.

The signal processing unit 320 may include a target tracking unit 331 using GPS.

The target tracking unit 331 uses a focused beamforming concept (technique) and a Global Positioning System (GPS) to remove a phase term of a signal remaining in the normalized data, and a desired target and measurement listening period can calculate the slope distance of .

The signal processing unit 320 may include a phase correction factor calculation unit 332 .

The phase correction factor calculator 332 obtains the curved wave time delay information based on the focused beamforming concept (technique) using Global Positioning System (GPS) information, and then performs phase correction as a weight vector. factor can be calculated.

Various embodiments of the present document include software (eg, a machine-readable storage media) (eg, a memory (internal memory or external memory)) that includes instructions stored in a readable storage medium (eg, a computer). : program) can be implemented. The device is a device capable of calling a stored command from a storage medium and operating according to the called command, and may include the electronic device according to the disclosed embodiments. When the command is executed by the control unit, the control unit may perform a function corresponding to the command directly or using other components under the control of the control unit. Instructions may include code generated or executed by a compiler or interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, non-transitory means that the storage medium does not include a signal and is tangible, but does not distinguish that data is semi-permanently or temporarily stored in the storage medium.

According to an embodiment, the method according to various embodiments disclosed in the present document may be included and provided in a computer program product.

According to an embodiment, there is provided a computer-readable recording medium storing a computer program, comprising: converting underwater radiation noise data measured from a desired target and a plurality of external targets into a digital signal using a plurality of hydroacoustic listeners; An operation of applying a band-pass filter, which is a cavitation frequency generation band, to the radiated noise digital signal and performing windowing according to a distribution among the plurality of hydroacoustic devices, and converting a time domain signal received by the hydroacoustic listener into a frequency domain signal Converting, normalizing to remove a magnitude term of the desired target signal included in the frequency domain signal, and using a global positioning system (GPS) in the normalized signal to obtain a desired target from the hydroacoustic listener After calculating the inter-inclination distance and orientation, obtaining the curved wave time delay information based on the concept of focused beamforming, the phase correction factor, which is a weight vector, is calculated. calculating, calculating the channel transfer function including the external target noise by calculating the weight vector on the normalized signal, introducing the concept of blind deconvolution to obtain the channel transfer function and the An operation of removing the external target noise and reconstructing a spectrum of a desired target signal using an artificial time reversal technique between frequency domain signals, an operation of reverse fast Fourier transforming the reconstructed spectrum into the time domain signal, and the time domain It may include instructions for causing the processor to perform a method including calculating an RMS value from the signal result and extracting propulsion system information of the external target by using a fast Fourier transform on the RMS value.

According to one embodiment, as a computer program stored in a computer-readable recording medium, the operation of converting the underwater radiation noise data measured from a desired target and a plurality of external targets using a plurality of hydroacoustic listeners into a digital signal; An operation of applying a band-pass filter, which is a cavitation frequency generation band, to the radiated noise digital signal and performing windowing according to a distribution among the plurality of hydroacoustic devices, and converting a time domain signal received by the hydroacoustic listener into a frequency domain signal Converting, normalizing to remove a magnitude term of the desired target signal included in the frequency domain signal, and using a global positioning system (GPS) in the normalized signal to obtain a desired target from the hydroacoustic listener After calculating the inter-inclination distance and orientation, obtaining the curved wave time delay information based on the concept of focused beamforming, the phase correction factor, which is a weight vector, is calculated. calculating, calculating the channel transfer function including the external target noise by calculating the weight vector on the normalized signal, introducing the concept of blind deconvolution to obtain the channel transfer function and the An operation of removing the external target noise and reconstructing a spectrum of a desired target signal using an artificial time reversal technique between frequency domain signals, an operation of reverse fast Fourier transforming the reconstructed spectrum into the time domain signal, and the time domain It may include instructions for causing the processor to perform a method including calculating an RMS value from the signal result and extracting propulsion system information of the external target by using a fast Fourier transform on the RMS value.

Although the above has been described with reference to the drawings and embodiments, it will be understood by those skilled in the art that various modifications and changes can be made to the embodiments without departing from the spirit of the embodiments described in the claims below. will be able

300: signal processing unit
301-1 to 301-n: desired target to nth target
310-1 to 310-n: first to nth hydroacoustic hearing instruments
320: signal processing unit
321: A/D converter
322: bandpass filter and windowing and frequency converter
323: normalization unit
324: channel transfer function estimator
325: desired target signal restoration unit
326: daemon signal output unit
330: location tracking unit

Claims (13)

converting underwater radiated noise data measured from a desired target and a plurality of external targets into digital signals using a plurality of hydroacoustic listeners;
applying a bandpass filter within a cavitation frequency generation band to the underwater radiated noise digital signal converted into the digital signal and performing windowing according to the distribution between the plurality of underwater acoustic listeners;
converting a time domain signal received by the hydroacoustic listener into a frequency domain signal;
normalizing to remove a magnitude term of the desired target signal included in the frequency domain signal;
After calculating the desired inclination distance and orientation between the targets from the hydroacoustic device by using a global positioning system (GPS) in the normalized signal, and obtaining curved wave time delay information based on a focused beamforming technique, Phase correction factor, which is a weight vector calculating;
calculating a channel transfer function including the external target noise by calculating the weight vector on the normalized signal;
removing the external target noise and reconstructing the spectrum of the desired target signal using an artificial time reversal technique between the channel transfer function and the frequency domain signal based on a blind deconvolution technique;
Inverse fast Fourier transforming the desired target signal from which the spectrum is reconstructed into the time domain signal;
calculating an effective value of the desired target signal converted into the time domain signal; and
Extracting the propulsion system information of the external target by using a fast Fourier transform on the RMS value
A signal processing method capable of removing external target noise when measuring radiated noise in the water, including a. According to claim 1,
The cavitation frequency band is 3 to 10 kHz, and the band pass filter performs filtering in 2 kHz to 4 kHz, 4 kHz to 8 kHz and 8 kHz to 10 kHz bands, and the windowing is performed using a Hanning window. Signal processing method capable of target noise cancellation. According to claim 1,
the frequency domain signal

The step of converting to is a signal processing method capable of removing external target noise when measuring underwater radiated noise calculated by Equation 1.
[Equation 1]

(here,

is the time domain signal received at the j-th receiver position of the listener array.

is the result value transformed into the frequency domain,

is the desired target position

Listener array group receiving from

second receiver position

represents the channel transfer function in

is the magnitude term of the desired target signal,

means the phase term of the desired target signal.) 4. The method of claim 3,
The normalizing step is a signal processing method capable of removing external target noise when measuring underwater radiated noise calculated by Equation 2 below.
[Equation 2]

(here,

means normalized signal) 5. The method of claim 4,
In the step of calculating the phase correction factor,
The slope distance WSSRc is calculated by Equation 3,
[Equation 3]

(Here, WSSRc is the inclination distance between the middle sensor and the target among the three or more measuring sensors, GPSR is the horizontal distance between the desired target and the measuring equipment calculated by the satellite navigation system, and Sensor _c is the middle sensor among the three or more measuring sensors. means depth)
Using the target and the inclination distance, the phase correction factor (

) is calculated,
[Equation 4]

here,

denotes a weight vector that includes information on the inclination distance and orientation between the target and the measuring equipment,

denotes an arbitrary phase shift, which means the sound line travel time of the sound wave transmitted between the desired target and the listeners)
Equations 5 and 6 are obtained by substituting Equation 3 into the weight vector Wj,
[Equation 5]

(where c is the average underwater sound velocity at

is the time delay value that is changed by the distance from the target and the measuring sensor,

is the delay time of the target signal received from the middle sensor to the sensor installed above,

represents the delay time of the target signal received from the middle sensor to the sensor installed below)
[Equation 6]

(here,

is derived simply by using a trigonometric function, and by substituting the slope distance (WSSRc) and azimuth information between the target and the measuring device calculated in Equation 3, the surface wave time delay according to the sensor can be calculated)
A signal processing method capable of removing external target noise when measuring radiated noise underwater to calculate the phase correction factor using Equations 5 and 6. 6. The method of claim 5,
The phase correction factor using Equations 5 and 6 is a signal processing method capable of removing external target noise when measuring underwater radiated noise determined by Equation 7.
[Equation 7]

(here,

The term has a linear phase characteristic and the inclination distance (

) is equivalent to the time delay caused by And due to the calculation of the weight vector Wj and the received signal, the target noise is amplified by the number of sensors and the external noise is reduced so that it is similar to the phase term of the target signal.

can be calculated) 7. The method of claim 6,
Calculating the channel transfer function comprises:
A signal processing method capable of estimating a channel transfer function using the normalized signal Dj(w) and the phase correction factor, and removing the external target noise when measuring the underwater radiated noise calculated by Equation 8 for the channel transfer function .
[Equation 8]

(here,

is the estimated transfer function) 8. The method of claim 7,
Restoring the spectrum of the desired target signal comprises:
Based on the blind deconvolution technique, the frequency domain signal (

and the transfer function (

to extract the spectral value using the time reversal technique, and

) is a signal processing method capable of removing external target noise when measuring underwater radiated noise calculated by Equation 8.
[Equation 8]

(here,

is the transfer function including the external target noise and time delay function

has been removed, and the time delay value caused by the inclination distance (WSSRc) between the target and the measuring device

with term and magnitude decay noise

The raw signal in the form with terms

The value from which the term was restored is restored.) According to claim 8,
The step of calculating the effective value is calculated by Equation 9,
[Equation 9]

(here, Z(D) means RMS)
The Z (D) is

A signal processing method that can remove external target noise when measuring radiated noise in the water, which calculates the effective value of the target signal by the number of times. 10. The method of claim 9,
Where N is a signal processing method capable of removing external target noise when measuring underwater radiated noise that is less than or equal to 0.05 seconds. An A/D converter for converting underwater radiation noise data measured from a desired target and a plurality of external targets using a plurality of hydroacoustic listeners into a digital signal;
A band-pass filter within the cavitation frequency generation band is applied to the underwater radiated noise digital signal converted into the digital signal, windowing is performed according to the distribution among the plurality of underwater acoustic listeners, and the time domain signal received by the underwater acoustic listener a bandpass filter and a frequency converter for converting a frequency domain signal;
a normalizer for removing a magnitude term of the desired target signal included in the frequency domain signal;
a target tracking unit for calculating a desired inclination distance and orientation between the targets from the hydroacoustic hearing device by using a global positioning system (GPS) in the normalized signal;
a phase correction factor calculator for calculating a phase correction factor, which is a weight vector, using a focused beamforming technique and information on a target inclination distance and orientation;
a channel transfer function estimator for calculating a channel transfer function including the external target noise by calculating the weight vector on the normalized signal;
a target signal restoration unit for removing the external target noise and reconstructing a spectrum of a desired target signal by using an artificial time reversal technique between the channel transfer function and the frequency domain signal based on a blind deconvolution technique; and
Inverse fast Fourier transform of the desired target signal from which the spectrum is reconstructed into the time domain signal, calculating an effective value of the desired target signal converted into the time domain signal, and using the fast Fourier transform on the effective value, the external target signal calculation unit to extract propulsion system information of
A signal processing device capable of removing external target noise when measuring radiated noise in the water, including a. As a computer-readable recording medium storing a computer program,
The computer program is
converting underwater radiated noise data measured from a desired target and a plurality of external targets into digital signals using a plurality of hydroacoustic listeners;
applying a band-pass filter within a cavitation frequency generation band to the underwater radiated noise digital signal converted into the digital signal and performing windowing according to the distribution between the plurality of underwater acoustic listeners;
converting a time domain signal received by the hydroacoustic listener into a frequency domain signal;
normalizing to remove a magnitude term of the desired target signal included in the frequency domain signal;
Calculate the desired inter-target inclination distance and orientation from the hydroacoustic device using a global positioning system (GPS) in the normalized signal, and use a focused beamforming technique and target inclination distance and orientation information to obtain a weight vector calculating a phase correction factor which is
calculating a channel transfer function including the external target noise by calculating the weight vector on the normalized signal;
removing the external target noise and reconstructing a spectrum of the desired target signal by using an artificial time reversal technique between the channel transfer function and the frequency domain signal based on a blind deconvolution technique;
inverse fast Fourier transforming the desired target signal from which the spectrum is restored into the time domain signal;
calculating an RMS value of the desired target signal converted into the time domain signal; and
A computer-readable recording medium comprising instructions for causing a processor to extract propulsion system information of the external target by using a fast Fourier transform on the RMS value. As a computer program stored in a computer-readable recording medium,
The computer program is
converting underwater radiated noise data measured from a desired target and a plurality of external targets into digital signals using a plurality of hydroacoustic listeners;
applying a band-pass filter within a cavitation frequency generation band to the underwater radiated noise digital signal converted into the digital signal and performing windowing according to the distribution between the plurality of underwater acoustic listeners;
converting a time domain signal received by the hydroacoustic listener into a frequency domain signal;
normalizing to remove a magnitude term of the desired target signal included in the frequency domain signal;
Calculate the desired inter-target inclination distance and orientation from the hydroacoustic device using a global positioning system (GPS) in the normalized signal, and use a focused beamforming technique and target inclination distance and orientation information to obtain a weight vector calculating a phase correction factor which is
calculating a channel transfer function including the external target noise by calculating the weight vector on the normalized signal;
removing the external target noise and reconstructing a spectrum of the desired target signal by using an artificial time reversal technique between the channel transfer function and the frequency domain signal based on a blind deconvolution technique;
inverse fast Fourier transforming the desired target signal from which the spectrum is restored into the time domain signal;
calculating an RMS value of the desired target signal converted into the time domain signal; and
A computer program comprising instructions for causing a processor to extract propulsion system information of the external target by using a fast Fourier transform on the RMS value.

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