Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535687
Yifei Wu, Yuwei Li
The performance of active sonar operating in shallow water is often limited by the reverberation level. If a target is moving relative to the reverberating scatters, the resulting Doppler effect from movement can be utilized to improve the detection of moving targets against stationary reverberation. In practice, the choice for Doppler processing is to use the Continuous waveform (CW) signal or one of its modifications. However, this narrow-band signal provides poor range resolution. This paper presents a novel Continuous waveform whose phase is coded by m-sequences, called BPSK signal. The BPSK signal is characterized by a comparable Doppler resolution as the CW signal, but with better range resolution. In this paper, the waveforms are composed of diverse pulses with a high duty ratio of up to 80%. These pulses are nearly orthogonal to each other. Sub-pulse processing is a method of breaking up the long-duration to achieve a faster update rate of the target scene. Increasing the number of sub-pulses increases the update rate, but the corresponding result will lead to a decrease in the Time Bandwidth Product, and be expected to reduce signal-to-reverberation ratio. The paper provides Doppler processing gain estimates and the theoretical prediction concerning BPSK signal are supported by simulation results.
{"title":"Sub-pulse processing of m-sequences phase-coded Continuous waveforms in shallow water","authors":"Yifei Wu, Yuwei Li","doi":"10.1109/COA.2016.7535687","DOIUrl":"https://doi.org/10.1109/COA.2016.7535687","url":null,"abstract":"The performance of active sonar operating in shallow water is often limited by the reverberation level. If a target is moving relative to the reverberating scatters, the resulting Doppler effect from movement can be utilized to improve the detection of moving targets against stationary reverberation. In practice, the choice for Doppler processing is to use the Continuous waveform (CW) signal or one of its modifications. However, this narrow-band signal provides poor range resolution. This paper presents a novel Continuous waveform whose phase is coded by m-sequences, called BPSK signal. The BPSK signal is characterized by a comparable Doppler resolution as the CW signal, but with better range resolution. In this paper, the waveforms are composed of diverse pulses with a high duty ratio of up to 80%. These pulses are nearly orthogonal to each other. Sub-pulse processing is a method of breaking up the long-duration to achieve a faster update rate of the target scene. Increasing the number of sub-pulses increases the update rate, but the corresponding result will lead to a decrease in the Time Bandwidth Product, and be expected to reduce signal-to-reverberation ratio. The paper provides Doppler processing gain estimates and the theoretical prediction concerning BPSK signal are supported by simulation results.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"296 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120923730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535745
Tian Tian, Han Hui, C. Jing
This study estimates the underwater structure acoustic radiation areas, mainly in the following aspects: analytical methods, boundary element and finite element, etc. This approach is a significant for mastery and understanding of the underwater structure vibration and radiation mechanism, calculations, theoretical estimates and acoustic design. From the engineering point of view, these algorithms are faced with a huge amount of numerical calculation, a long calculation time, and frequency band is limited and other issues. A method is brought forward to estimate acoustic radiation based on vibration data from underwater structures. On the assumption that there is some transfer function relationship between underwater structure radiated noise and vibration monitoring data, the relation is multi-input, single-output and convergent, and the method of exponentially-weighted is adopted. Firstly, according to the thin shell equation and wave equation, we establish a large-scale cylindrical shell vibration/radiation model; simulate resonance relation of vibration monitoring data and acoustic radiation; and verify the method of data weighting. Then, we explain that the estimation error of acoustic radiation decreases when the number of monitoring points and the sample size increase; and, that the error will remain within a range of 3dB when the increase reaches a certain level. Finally, through the verification of ship measurement vibration monitoring and acoustic radiation data, the estimated value and the true value have a good consistency. This method has a small calculating burden and a fast speed, and it is also both reasonable and feasible. It is possible to apply the method to an engineering estimation.
{"title":"A research on underwater structure acoustic radiation estimation based on vibration data","authors":"Tian Tian, Han Hui, C. Jing","doi":"10.1109/COA.2016.7535745","DOIUrl":"https://doi.org/10.1109/COA.2016.7535745","url":null,"abstract":"This study estimates the underwater structure acoustic radiation areas, mainly in the following aspects: analytical methods, boundary element and finite element, etc. This approach is a significant for mastery and understanding of the underwater structure vibration and radiation mechanism, calculations, theoretical estimates and acoustic design. From the engineering point of view, these algorithms are faced with a huge amount of numerical calculation, a long calculation time, and frequency band is limited and other issues. A method is brought forward to estimate acoustic radiation based on vibration data from underwater structures. On the assumption that there is some transfer function relationship between underwater structure radiated noise and vibration monitoring data, the relation is multi-input, single-output and convergent, and the method of exponentially-weighted is adopted. Firstly, according to the thin shell equation and wave equation, we establish a large-scale cylindrical shell vibration/radiation model; simulate resonance relation of vibration monitoring data and acoustic radiation; and verify the method of data weighting. Then, we explain that the estimation error of acoustic radiation decreases when the number of monitoring points and the sample size increase; and, that the error will remain within a range of 3dB when the increase reaches a certain level. Finally, through the verification of ship measurement vibration monitoring and acoustic radiation data, the estimated value and the true value have a good consistency. This method has a small calculating burden and a fast speed, and it is also both reasonable and feasible. It is possible to apply the method to an engineering estimation.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127417338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535727
Lan Hualin, Li Rui, Zuo Chunli, Li Di
The direction of an underwater target can be estimated by one seabed linear horizontal hydrophone array via analysis of the received target acoustic data. Because the estimated direction is referenced to the linear array coordinate, the direction of the linear array should first be determined in order to derive the absolute direction of the underwater target as referenced to the north. Generally, the direction of the linear array can be obtained by an instrument such as compass installed on the array. Unfortunately, when there is no compass some other underwater acoustic method must be designed to estimate the direction of the linear array. A calibration method of the direction of linear array is proposed in this paper when there is no compass installed. Firstly, the location of the array is measured by GPS when the array is deployed. Then an acoustic signal is transmitted at several different locations while the location is measured by GPS The relative direction of the acoustic signal can be estimated by the horizontal hydrophone array. By combining the relative directions estimated by acoustic data and the absolute direction as measured by GPS, the direction of the array can finally be estimated. Because of the effect of the varying source position to the direction of the linear array, the selection of the measured position has to be considered carefully. Furthermore, the effect of the ambiguous direction of the linear array is considered in the paper and its performance is analyzed. The proposed method is validated by simulation and lake trial data processing. The effect of the signal-to-noise ratio on the direction estimation is considered, and the results show that the direction estimation accuracy is relatively close, with the signalto noise ratio and the number of the array elements.
{"title":"Calibration of the direction of a linear horizontal hydrophone array on the sea bottom","authors":"Lan Hualin, Li Rui, Zuo Chunli, Li Di","doi":"10.1109/COA.2016.7535727","DOIUrl":"https://doi.org/10.1109/COA.2016.7535727","url":null,"abstract":"The direction of an underwater target can be estimated by one seabed linear horizontal hydrophone array via analysis of the received target acoustic data. Because the estimated direction is referenced to the linear array coordinate, the direction of the linear array should first be determined in order to derive the absolute direction of the underwater target as referenced to the north. Generally, the direction of the linear array can be obtained by an instrument such as compass installed on the array. Unfortunately, when there is no compass some other underwater acoustic method must be designed to estimate the direction of the linear array. A calibration method of the direction of linear array is proposed in this paper when there is no compass installed. Firstly, the location of the array is measured by GPS when the array is deployed. Then an acoustic signal is transmitted at several different locations while the location is measured by GPS The relative direction of the acoustic signal can be estimated by the horizontal hydrophone array. By combining the relative directions estimated by acoustic data and the absolute direction as measured by GPS, the direction of the array can finally be estimated. Because of the effect of the varying source position to the direction of the linear array, the selection of the measured position has to be considered carefully. Furthermore, the effect of the ambiguous direction of the linear array is considered in the paper and its performance is analyzed. The proposed method is validated by simulation and lake trial data processing. The effect of the signal-to-noise ratio on the direction estimation is considered, and the results show that the direction estimation accuracy is relatively close, with the signalto noise ratio and the number of the array elements.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132633303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535725
Bingqing Li, Guanghui Ren, Zhongshu Pan, Tingting Teng
As a key technology of detection and tracking system, moving target detection and tracking has attracted a great deal of attention. To achieve the goal of tracking target, conventional methods have to complete the detection of targets firstly, and then track the target. However, such kind of approaches require using the method of constant false-alarm rate to detect the whole frame image received at that time, which not only reduces the detection efficiency but also degrades the performance of target tracking. In order to implement real-time monitoring divers and other small moving targets under the conditions of strong underwater noise and clutter interference, an interactive algorithm for moving target detection and tracking is proposed based on acoustic image, which jointly analyzes the target detection system and the target tracking system. In the target tracking unit, the interactive algorithm takes advantage of data interconnection to remove the false targets produced by target detection; extrapolates the target's track, and predicts the location that the target may appear at the next moment by employing the Kalman filter. These messages will be used as priori information in the detection unit. In the detection unit, first of all, a gate is established whose center is the position that the target tracking unit predicted. For the image received at the next moment, detection in the predicted gate in implemented by using the method of constant false-alarm rate, followed by feeding back the detection results to the tracking unit. Compared with existed methods, the proposed algorithm can effectively improve the target detection efficiency and tracking performance, providing a better approach to monitor underwater small targets.
{"title":"Moving target detection and tracking interactive algorithm based on acoustic image","authors":"Bingqing Li, Guanghui Ren, Zhongshu Pan, Tingting Teng","doi":"10.1109/COA.2016.7535725","DOIUrl":"https://doi.org/10.1109/COA.2016.7535725","url":null,"abstract":"As a key technology of detection and tracking system, moving target detection and tracking has attracted a great deal of attention. To achieve the goal of tracking target, conventional methods have to complete the detection of targets firstly, and then track the target. However, such kind of approaches require using the method of constant false-alarm rate to detect the whole frame image received at that time, which not only reduces the detection efficiency but also degrades the performance of target tracking. In order to implement real-time monitoring divers and other small moving targets under the conditions of strong underwater noise and clutter interference, an interactive algorithm for moving target detection and tracking is proposed based on acoustic image, which jointly analyzes the target detection system and the target tracking system. In the target tracking unit, the interactive algorithm takes advantage of data interconnection to remove the false targets produced by target detection; extrapolates the target's track, and predicts the location that the target may appear at the next moment by employing the Kalman filter. These messages will be used as priori information in the detection unit. In the detection unit, first of all, a gate is established whose center is the position that the target tracking unit predicted. For the image received at the next moment, detection in the predicted gate in implemented by using the method of constant false-alarm rate, followed by feeding back the detection results to the tracking unit. Compared with existed methods, the proposed algorithm can effectively improve the target detection efficiency and tracking performance, providing a better approach to monitor underwater small targets.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"509 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123202329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535634
Liu Shuang, Lan Yu, Zhou Tianfang
An acoustic vector sensor can directly measure particle velocity or acceleration under water. Its directivity is a cosine pattern in the working frequency band. And its array gain can achieve 4.8 dB to 6 dB. An acoustic dyadic sensor can be used in order to make the directivity of the acoustic vector sensor sharper, and to measure the gradient of velocity or acceleration under the water. And its directivity is the quadrupole's directivity; and, the directivity function is the square of cosine or cosine multiplied by sine. Its array gain can achieve 6 dB to 9.5 dB. Usually an acoustic dyadic sensor is made of a vector hydrophone array, or a number of neutral buoyancy velocity sensors or accelerators are mounted at a certain positional relationship to form an acoustic dyadic sensor. The gradient of velocity or acceleration can be obtained by subtracting signals from two velocity sensors or accelerators. When designing an acoustic dyadic sensor, the distance of velocity sensors or accelerators must be taken into consideration because this influences the working bandwidth. When an acoustic dyadic sensor is made of accelerators, the slope of the sensitivity is 12 decibels per octave. So the working frequency is lower, and the sensitivity becomes smaller. Acoustic dyadic sensors usually cannot work at a very low frequency because of the low signal tonoise ratio. are very small compared to the wavelength. The acoustic pressure-gradient can be calculated by subtraction of signals from the two hydrophones. So it is an indirect measurement of acoustic vector signals under the water. The second type is usually the co oscillating vector hydrophone. This kind of acoustic vector sensor is usually built by mounting a velocity sensor or a accelerometer in a spherical or cylindrical shell body, or in a neutrally buoyant materials which is made by fIlling an amount of hollow glassmicroballoons in a base material of epoxy resin. The suspension system is usually needed to suspend the hydrophone. And it can directly measure the acoustic vector signals under the water. No matter which kind of acoustic vector sensor is used, its directivity is a cosine pattern in the working band. Its array gain can achieve 4.8 dB-6 dB. An acoustic dyadic sensor can be regarded as an advanced form of acoustic vector sensor. It can measure the second order gradient of acoustic pressure; and the gradient of velocity or acceleration under the water. Its working principle is similar to the acoustic vector sensor. However, it takes advantage of finite difference approximation. Usually an acoustic dyadic sensor is comprised of an acoustic vector sensor array, or a number of neutral buoyancy velocity sensors or accelerators which are mounted in a certain positional relationship. Such an array gain can achieve 6dB to 9.5dB. In this paper an acoustic dyadic sensor is designed comprising accelerators, and it can be directly installed on the underwater platform. The accelerators are mounted in a
{"title":"Theory and design of acoustic dyadic sensor","authors":"Liu Shuang, Lan Yu, Zhou Tianfang","doi":"10.1109/COA.2016.7535634","DOIUrl":"https://doi.org/10.1109/COA.2016.7535634","url":null,"abstract":"An acoustic vector sensor can directly measure particle velocity or acceleration under water. Its directivity is a cosine pattern in the working frequency band. And its array gain can achieve 4.8 dB to 6 dB. An acoustic dyadic sensor can be used in order to make the directivity of the acoustic vector sensor sharper, and to measure the gradient of velocity or acceleration under the water. And its directivity is the quadrupole's directivity; and, the directivity function is the square of cosine or cosine multiplied by sine. Its array gain can achieve 6 dB to 9.5 dB. Usually an acoustic dyadic sensor is made of a vector hydrophone array, or a number of neutral buoyancy velocity sensors or accelerators are mounted at a certain positional relationship to form an acoustic dyadic sensor. The gradient of velocity or acceleration can be obtained by subtracting signals from two velocity sensors or accelerators. When designing an acoustic dyadic sensor, the distance of velocity sensors or accelerators must be taken into consideration because this influences the working bandwidth. When an acoustic dyadic sensor is made of accelerators, the slope of the sensitivity is 12 decibels per octave. So the working frequency is lower, and the sensitivity becomes smaller. Acoustic dyadic sensors usually cannot work at a very low frequency because of the low signal tonoise ratio. are very small compared to the wavelength. The acoustic pressure-gradient can be calculated by subtraction of signals from the two hydrophones. So it is an indirect measurement of acoustic vector signals under the water. The second type is usually the co oscillating vector hydrophone. This kind of acoustic vector sensor is usually built by mounting a velocity sensor or a accelerometer in a spherical or cylindrical shell body, or in a neutrally buoyant materials which is made by fIlling an amount of hollow glassmicroballoons in a base material of epoxy resin. The suspension system is usually needed to suspend the hydrophone. And it can directly measure the acoustic vector signals under the water. No matter which kind of acoustic vector sensor is used, its directivity is a cosine pattern in the working band. Its array gain can achieve 4.8 dB-6 dB. An acoustic dyadic sensor can be regarded as an advanced form of acoustic vector sensor. It can measure the second order gradient of acoustic pressure; and the gradient of velocity or acceleration under the water. Its working principle is similar to the acoustic vector sensor. However, it takes advantage of finite difference approximation. Usually an acoustic dyadic sensor is comprised of an acoustic vector sensor array, or a number of neutral buoyancy velocity sensors or accelerators which are mounted in a certain positional relationship. Such an array gain can achieve 6dB to 9.5dB. In this paper an acoustic dyadic sensor is designed comprising accelerators, and it can be directly installed on the underwater platform. The accelerators are mounted in a ","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"514 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123203181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535707
Mei Jidan, Z. Yinghui, Ma Chao, Xu Fulian
For surface ships, the towed hydrophones array is usually used to detect azimuth and to track moving targets because of its large aperture. The effective scope of a common sound pressure single array is only 180°, so that the common array cannot determine whether a target is to the left or to the right. While a twin-line array has similarity with a planar array in theory, a twin-line array does have the ability to discriminate between port/starboard. In order for the twin-line array to make post/starboard discrimination, a time delayed addition method and time delayed subtraction method are widely applied in direction finding field. Time-delay addition method obtains bearing time results by adding beam forming outputs, while its post/starboard suppression ratio is small. Time-delay subtraction method, obtains bearing time results by subtracting beam forming outputs. Its post/starboard discrimination ability will decline sharply under the condition of low SNR or where shape distortion of the array existing. Based on the above two algorithms, further research which subtracts bearing time results could obtain new bearing time results and improve post/starboard discrimination ability in low SNR conditions. Furthermore, the shape distortion effect on the performance of this algorithm is also studied in this paper. This paper mainly studied three kinds of influences of shape distortion on post/starboard discrimination ability of the algorithm: twin-line parallel displacement distortion, nonparallel displacement distortion; and, circular arc shape distortion. The experimental simulation results show that shape distortion does influence post/starboard discrimination ability seriously, while the discrimination ability can be recovered well after modification. Therefore, it is necessary to study shape distortion measurement methods and adaptive shape distortion modification algorithms.
{"title":"Research on the post/starboard discrimination algorithm for twin-line array and the influence of array shape distortion","authors":"Mei Jidan, Z. Yinghui, Ma Chao, Xu Fulian","doi":"10.1109/COA.2016.7535707","DOIUrl":"https://doi.org/10.1109/COA.2016.7535707","url":null,"abstract":"For surface ships, the towed hydrophones array is usually used to detect azimuth and to track moving targets because of its large aperture. The effective scope of a common sound pressure single array is only 180°, so that the common array cannot determine whether a target is to the left or to the right. While a twin-line array has similarity with a planar array in theory, a twin-line array does have the ability to discriminate between port/starboard. In order for the twin-line array to make post/starboard discrimination, a time delayed addition method and time delayed subtraction method are widely applied in direction finding field. Time-delay addition method obtains bearing time results by adding beam forming outputs, while its post/starboard suppression ratio is small. Time-delay subtraction method, obtains bearing time results by subtracting beam forming outputs. Its post/starboard discrimination ability will decline sharply under the condition of low SNR or where shape distortion of the array existing. Based on the above two algorithms, further research which subtracts bearing time results could obtain new bearing time results and improve post/starboard discrimination ability in low SNR conditions. Furthermore, the shape distortion effect on the performance of this algorithm is also studied in this paper. This paper mainly studied three kinds of influences of shape distortion on post/starboard discrimination ability of the algorithm: twin-line parallel displacement distortion, nonparallel displacement distortion; and, circular arc shape distortion. The experimental simulation results show that shape distortion does influence post/starboard discrimination ability seriously, while the discrimination ability can be recovered well after modification. Therefore, it is necessary to study shape distortion measurement methods and adaptive shape distortion modification algorithms.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124119403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535786
Tongwei Zhang, Yang Kunde, Liu Yeyao, Yang Bo
Ambient noise in the ocean has been measured and studied for over half a century. Due to multipath effects, the signal will not always arrive from the horizontal direction. The directional response of a vertical line array (VLA) to a distant source can be expressed in terms of the modal beams weighted by their normal mode amplitudes. This modal representation offers a physical interpretation of the vertical directionality of the source in terms of normal modes. When a short VLA lies at the lower sound speed portion of the water column and a high frequency source is located at the higher sound speed portion of the water column, there always exists a notch in the horizontal direction. The vertical directionality of the source has been validated using Mediterranean Sea data, and it is shown that the vertical directionalities of the ambient noise and the distant source are quite different.
{"title":"Vertical directionality of a source observed by a short vertical line array in shallow water","authors":"Tongwei Zhang, Yang Kunde, Liu Yeyao, Yang Bo","doi":"10.1109/COA.2016.7535786","DOIUrl":"https://doi.org/10.1109/COA.2016.7535786","url":null,"abstract":"Ambient noise in the ocean has been measured and studied for over half a century. Due to multipath effects, the signal will not always arrive from the horizontal direction. The directional response of a vertical line array (VLA) to a distant source can be expressed in terms of the modal beams weighted by their normal mode amplitudes. This modal representation offers a physical interpretation of the vertical directionality of the source in terms of normal modes. When a short VLA lies at the lower sound speed portion of the water column and a high frequency source is located at the higher sound speed portion of the water column, there always exists a notch in the horizontal direction. The vertical directionality of the source has been validated using Mediterranean Sea data, and it is shown that the vertical directionalities of the ambient noise and the distant source are quite different.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"05 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129316073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535789
Qi Jie, Sun Weitao, Sun Haixin, Lin Congren, Yao Guangtao
This paper proposes method of detecting the motion state of underwater targets based on compression sensing. A Linear frequency modulation signal is influenced by the moving state of the target under test, and its echo parameters such as the initial frequency, frequency modulation rate, and phase, will change according to the moving state of the target. Firstly, this method uses the characteristics of the high order LFM Chirplet Transform matrix, which has the bending effect, and energy accumulation in the time-frequency domain, in order to sparse the linear frequency modulated echo signal. Secondly, based on compression sensing, the characteristic parameters of an echo signal, such as the initial frequency and frequency modulation rate, have been reconstructed. At the same time, the interference by background noise in the underwater acoustic channel is eliminated. As a result, we can determine the motion state of an underwater object according to the physical characteristics of the linear frequency modulation signal echo. Simulations and experiments show that the higher order Chirplet Transform has very high resolution without cross-term inference, and is suitable for analyzing non-stationary underwater acoustic signals. After obtaining the characteristics of the time-frequency of an echo signal, the main characteristics of the data are extracted by compressed sensing based on the Noiselets matrix, and the noise interference from the underwater acoustic channel is eliminated. This technique can improve measurement of the physical parameters of underwater moving targets, and has a high detection probability under low SNR, so the validity of the theoretical analysis has been proved.
{"title":"Detection of underwater moving object based on the compressed sensing","authors":"Qi Jie, Sun Weitao, Sun Haixin, Lin Congren, Yao Guangtao","doi":"10.1109/COA.2016.7535789","DOIUrl":"https://doi.org/10.1109/COA.2016.7535789","url":null,"abstract":"This paper proposes method of detecting the motion state of underwater targets based on compression sensing. A Linear frequency modulation signal is influenced by the moving state of the target under test, and its echo parameters such as the initial frequency, frequency modulation rate, and phase, will change according to the moving state of the target. Firstly, this method uses the characteristics of the high order LFM Chirplet Transform matrix, which has the bending effect, and energy accumulation in the time-frequency domain, in order to sparse the linear frequency modulated echo signal. Secondly, based on compression sensing, the characteristic parameters of an echo signal, such as the initial frequency and frequency modulation rate, have been reconstructed. At the same time, the interference by background noise in the underwater acoustic channel is eliminated. As a result, we can determine the motion state of an underwater object according to the physical characteristics of the linear frequency modulation signal echo. Simulations and experiments show that the higher order Chirplet Transform has very high resolution without cross-term inference, and is suitable for analyzing non-stationary underwater acoustic signals. After obtaining the characteristics of the time-frequency of an echo signal, the main characteristics of the data are extracted by compressed sensing based on the Noiselets matrix, and the noise interference from the underwater acoustic channel is eliminated. This technique can improve measurement of the physical parameters of underwater moving targets, and has a high detection probability under low SNR, so the validity of the theoretical analysis has been proved.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117310797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535643
M. Irshad, Hangfang Zhao, Wen Xu
Matched-field processing (MFP) for source localization usually experiences shortcomings such as low resolution and high computational workload. In this paper, a high resolution matched-field source localization method based on sparse reconstruction algorithms is presented. The underwater source localization problem is represented by solving an underdetermined linear equation. By enforcing the spatial sparsity of source signals, the signal strength on a specified grid is evaluated using sparse reconstruction algorithms. Focusing on the case of multiple snapshots, the system's equation based on the data correlation matrix is established, which increases the ratio of measurements to sparsity (RMS) and reduces the problem dimensionality to the minimum. Besides, the system equation can be equivalent to a Bartlett processor, thus the proposed method can achieve robust estimation as effectively as Bartlett but with better resolution.
{"title":"High resolution matched-field source localization based on sparse-reconstruction","authors":"M. Irshad, Hangfang Zhao, Wen Xu","doi":"10.1109/COA.2016.7535643","DOIUrl":"https://doi.org/10.1109/COA.2016.7535643","url":null,"abstract":"Matched-field processing (MFP) for source localization usually experiences shortcomings such as low resolution and high computational workload. In this paper, a high resolution matched-field source localization method based on sparse reconstruction algorithms is presented. The underwater source localization problem is represented by solving an underdetermined linear equation. By enforcing the spatial sparsity of source signals, the signal strength on a specified grid is evaluated using sparse reconstruction algorithms. Focusing on the case of multiple snapshots, the system's equation based on the data correlation matrix is established, which increases the ratio of measurements to sparsity (RMS) and reduces the problem dimensionality to the minimum. Besides, the system equation can be equivalent to a Bartlett processor, thus the proposed method can achieve robust estimation as effectively as Bartlett but with better resolution.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114326917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-08DOI: 10.1109/COA.2016.7535652
Tan Ke, Xu Xiaonan, Bian Hongyu
Image matching technology is an important part of image processing technology. In this paper, the normal distributions transform (NDT) image matching algorithm and its application in the sonar image processing is studied. The NDT algorithm is based on a probability model. It calculates the coordinate of the image of the target point instead of the grey value, and this speeds up the sonar image matching process. Previously, before image matching was available, per-processing of the sonar image was necessary. The research of pre-processing of sonar imaging concerns noise reduction and image segmentation of the sonar image. Several classical methods of sonar image noise reduction are studied. The advantages and disadvantages of each method are analyzed. Based on a kind of DSP chip, the NDT image matching algorithm is achieved.
{"title":"The application of NDT algorithm in sonar image processing","authors":"Tan Ke, Xu Xiaonan, Bian Hongyu","doi":"10.1109/COA.2016.7535652","DOIUrl":"https://doi.org/10.1109/COA.2016.7535652","url":null,"abstract":"Image matching technology is an important part of image processing technology. In this paper, the normal distributions transform (NDT) image matching algorithm and its application in the sonar image processing is studied. The NDT algorithm is based on a probability model. It calculates the coordinate of the image of the target point instead of the grey value, and this speeds up the sonar image matching process. Previously, before image matching was available, per-processing of the sonar image was necessary. The research of pre-processing of sonar imaging concerns noise reduction and image segmentation of the sonar image. Several classical methods of sonar image noise reduction are studied. The advantages and disadvantages of each method are analyzed. Based on a kind of DSP chip, the NDT image matching algorithm is achieved.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125158357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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