Pub Date : 1900-01-01DOI: 10.1109/COA.2016.7535736
W. Wenbo, Li Sichun, Y. Jianshe, Liu Zhao, Zhou Weicun
In recent years, scientists have been paying more and more attention on extracting features from the radiated noise of underwater targets. Thus, enriching the feature reserve of underwater targets is quite significant for scientists in order to detect and study them. The paper presents an algorithm of feature extraction, which focuses on the MFCC feature coefficients of underwater targets. Mel Frequency Cepstral Coefficients (MFCCs) are based on the nonlinear frequency feature of human ears. In essence, MFCC works via selecting energy in different frequency bands as the feature of target. Because of its outstanding performance in expressing speech spectrum at low frequency, since it is a good simulation of human auditory sensation, it has been one of the most important features used in speaker recognition systems. However, whether it is applicable in the case of expressing the features of underwater targets was still unclear. According to the result of a series of correlative experiments and researches, scientists found that the principle of distinguishing different underwater radiated noises by sonarman is the same as voice recognition by human ears. Meanwhile, the method of extracting MFCC has some advantages. For example, noises at low frequencies (in the audible range), which are the main sources of radiated noises ships and submarines, can propagate for a long distance. Fortunately, the method of extracting MFCC is robust to resist the disturbance of background noise at that frequency band. At the same time, seas and oceans always have chaotic background noise. The acoustic processes underwater are usually very complicated and nonlinear, and therefore requiring a proper nonlinear principle. Thus, MFCC can be applied to feature extraction of underwater radiated noises. In this paper, the radiated noises of different marine lifes (whales, sea lions and dolphins ), divers, boats and ships are all researched. Their MFCC feature coefficients are extracted and compared. The results show that different targets have clear differences in MFCC feature coefficients. Therefore, MFCC can be an effective feature for extraction and recognition.
{"title":"Feature extraction of underwater target in auditory sensation area based on MFCC","authors":"W. Wenbo, Li Sichun, Y. Jianshe, Liu Zhao, Zhou Weicun","doi":"10.1109/COA.2016.7535736","DOIUrl":"https://doi.org/10.1109/COA.2016.7535736","url":null,"abstract":"In recent years, scientists have been paying more and more attention on extracting features from the radiated noise of underwater targets. Thus, enriching the feature reserve of underwater targets is quite significant for scientists in order to detect and study them. The paper presents an algorithm of feature extraction, which focuses on the MFCC feature coefficients of underwater targets. Mel Frequency Cepstral Coefficients (MFCCs) are based on the nonlinear frequency feature of human ears. In essence, MFCC works via selecting energy in different frequency bands as the feature of target. Because of its outstanding performance in expressing speech spectrum at low frequency, since it is a good simulation of human auditory sensation, it has been one of the most important features used in speaker recognition systems. However, whether it is applicable in the case of expressing the features of underwater targets was still unclear. According to the result of a series of correlative experiments and researches, scientists found that the principle of distinguishing different underwater radiated noises by sonarman is the same as voice recognition by human ears. Meanwhile, the method of extracting MFCC has some advantages. For example, noises at low frequencies (in the audible range), which are the main sources of radiated noises ships and submarines, can propagate for a long distance. Fortunately, the method of extracting MFCC is robust to resist the disturbance of background noise at that frequency band. At the same time, seas and oceans always have chaotic background noise. The acoustic processes underwater are usually very complicated and nonlinear, and therefore requiring a proper nonlinear principle. Thus, MFCC can be applied to feature extraction of underwater radiated noises. In this paper, the radiated noises of different marine lifes (whales, sea lions and dolphins ), divers, boats and ships are all researched. Their MFCC feature coefficients are extracted and compared. The results show that different targets have clear differences in MFCC feature coefficients. Therefore, MFCC can be an effective feature for extraction and recognition.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131495980","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 : 1900-01-01DOI: 10.1109/COA.2016.7535771
S. Jesus
Seismic inversion with an AUV-based sensor array system is an appealing concept that opens up a number of interesting possibilities but faces also a number of technological and scientific challenges. Among the technological challenges there is the fact that sensor arrays are no longer hardwired to the tow ship and therefore on the fly data monitoring imposes stringent restrictions on the amount of data that can be sent to the support ship. One of the scientific challenges is to determine the optimal sensor array configuration by exploring AUV mobility for inverting the bottom geophysical structure of interest. In fact, the industry standard long planar array and the associated acoustic data processing may not be the setup with the highest performance for each scenario at hand. Generic optimization of sensor distribution through space has been a long standing problem to which there are no closed form solutions. Generically speaking, field diversity maximization is often referred to as a criteria for sensor positioning. This work explores data incoherence as a possible criteria to derive performance of distributed sensor arrays. Additional technological limitations such as array aperture, number of sensors and distances between vehicles impose additional constraints leading to suboptimal configurations. Compressed sensing array processing is used both to explore data incoherence and to offer data reduction for alleviating on the fly monitoring.
{"title":"Distributed sensor array for bottom inversion","authors":"S. Jesus","doi":"10.1109/COA.2016.7535771","DOIUrl":"https://doi.org/10.1109/COA.2016.7535771","url":null,"abstract":"Seismic inversion with an AUV-based sensor array system is an appealing concept that opens up a number of interesting possibilities but faces also a number of technological and scientific challenges. Among the technological challenges there is the fact that sensor arrays are no longer hardwired to the tow ship and therefore on the fly data monitoring imposes stringent restrictions on the amount of data that can be sent to the support ship. One of the scientific challenges is to determine the optimal sensor array configuration by exploring AUV mobility for inverting the bottom geophysical structure of interest. In fact, the industry standard long planar array and the associated acoustic data processing may not be the setup with the highest performance for each scenario at hand. Generic optimization of sensor distribution through space has been a long standing problem to which there are no closed form solutions. Generically speaking, field diversity maximization is often referred to as a criteria for sensor positioning. This work explores data incoherence as a possible criteria to derive performance of distributed sensor arrays. Additional technological limitations such as array aperture, number of sensors and distances between vehicles impose additional constraints leading to suboptimal configurations. Compressed sensing array processing is used both to explore data incoherence and to offer data reduction for alleviating on the fly monitoring.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121622298","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 : 1900-01-01DOI: 10.1109/COA.2016.7535659
Yue Sun, Jintao Wang, Longzhuang He
Multiple-input multiple-output (MIMO) is considered to be the key technology to improve the spectral efficiency for underwater acoustic communication (UAC) systems. As a novel architecture of MIMO system, space shift keying (SSK) is proposed to improve the energy efficiency comparing with traditional MIMO architecture. In this paper, the Lagrange multiplier method (LMM) is applied to solve the power allocation problem in SSK system, and a genetic based heuristic method is proposed to provide superior performance of symbol error rate (SER). Comparing with other prescaling techniques of SSK, such as multi-antenna space modulation (MSMod) and modified SSK (MSSK), the genetic based heuristic method can keep the benefits of SSK, while having a lower computational complexity at the receiver. The Monte Carlo simulation results are shown to verify the SER performance of this proposed method.
{"title":"Power allocation for space shift keying in underwater acoustic communication","authors":"Yue Sun, Jintao Wang, Longzhuang He","doi":"10.1109/COA.2016.7535659","DOIUrl":"https://doi.org/10.1109/COA.2016.7535659","url":null,"abstract":"Multiple-input multiple-output (MIMO) is considered to be the key technology to improve the spectral efficiency for underwater acoustic communication (UAC) systems. As a novel architecture of MIMO system, space shift keying (SSK) is proposed to improve the energy efficiency comparing with traditional MIMO architecture. In this paper, the Lagrange multiplier method (LMM) is applied to solve the power allocation problem in SSK system, and a genetic based heuristic method is proposed to provide superior performance of symbol error rate (SER). Comparing with other prescaling techniques of SSK, such as multi-antenna space modulation (MSMod) and modified SSK (MSSK), the genetic based heuristic method can keep the benefits of SSK, while having a lower computational complexity at the receiver. The Monte Carlo simulation results are shown to verify the SER performance of this proposed method.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726077","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 : 1900-01-01DOI: 10.1109/COA.2016.7535695
Ming Yue, Y. R. Zheng, Zhenrui Chen, Yunfeng Han
This paper proposes a low-complexity dual pseudorandom noise (PN) scheme for identity (ID) detection and coarse frame synchronization. The two PN sequences are identical and are separated by a specified length of gap which serves as the ID for different sensor nodes. The receiver ID detection is implemented on a microcontroller MSP430F5529 by calculating the correlation between the two segments of the received signal with the specified separation gap. When the gap length is matched with the ID, the correlator outputs a peak which sets the wakeup enable. The time index of the correlator peak is used as the coarse synchronization of the data frame. An iterative algorithm is used that requires only one multiplication and two additions for each sample input regardless of the length of the PN sequences, thus achieving low computational complexity. The proposed dual PN detection scheme has been successfully tested by simulated fading channels and real-world measured channels. The results show that, in long multipath channels with more than 60 taps, the proposed scheme achieves high detection rate and low false alarm rate using maximal-length sequences as short as 31 bits to 127 bits, therefore it is suitable as a low-power wake-up receiver.
{"title":"Microcontroller implementation of low-complexity wake-up receiver for wireless sensor nodes in severe multipath fading channels","authors":"Ming Yue, Y. R. Zheng, Zhenrui Chen, Yunfeng Han","doi":"10.1109/COA.2016.7535695","DOIUrl":"https://doi.org/10.1109/COA.2016.7535695","url":null,"abstract":"This paper proposes a low-complexity dual pseudorandom noise (PN) scheme for identity (ID) detection and coarse frame synchronization. The two PN sequences are identical and are separated by a specified length of gap which serves as the ID for different sensor nodes. The receiver ID detection is implemented on a microcontroller MSP430F5529 by calculating the correlation between the two segments of the received signal with the specified separation gap. When the gap length is matched with the ID, the correlator outputs a peak which sets the wakeup enable. The time index of the correlator peak is used as the coarse synchronization of the data frame. An iterative algorithm is used that requires only one multiplication and two additions for each sample input regardless of the length of the PN sequences, thus achieving low computational complexity. The proposed dual PN detection scheme has been successfully tested by simulated fading channels and real-world measured channels. The results show that, in long multipath channels with more than 60 taps, the proposed scheme achieves high detection rate and low false alarm rate using maximal-length sequences as short as 31 bits to 127 bits, therefore it is suitable as a low-power wake-up receiver.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123913636","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 : 1900-01-01DOI: 10.1109/COA.2016.7535747
Zhang Youwen, Hong Xiaoping, W. Yonggang, Sun Da-jun
The Frequency Hopping (FH) communication technique is one of classical methods of spread spectrum communication techniques, and it is widely used in terrestrial and underwater communications due to its robustness to jamming, low probability of interception and facility in communication networking. In particular, estimating and tracking the parameters of FH signals are important tasks in underwater acoustic warfare. This paper applies gridless SPICE (GLS) to the parameter estimation of underwater acoustic FH signals, mainly focused on time-frequency pattern and hop timing. As compared to the conventional spectrogram method, the time-frequency analysis method based on gridless SPICE has better frequency acquisition for the same samples. As compared to the SLR method proposed by Daniele Angelosante, this method has better performance for estimating parameters when we do not know the hopping frequency set.
{"title":"Gridless SPICE applied to parameter estimation of underwater acoustic Frequency Hopping signals","authors":"Zhang Youwen, Hong Xiaoping, W. Yonggang, Sun Da-jun","doi":"10.1109/COA.2016.7535747","DOIUrl":"https://doi.org/10.1109/COA.2016.7535747","url":null,"abstract":"The Frequency Hopping (FH) communication technique is one of classical methods of spread spectrum communication techniques, and it is widely used in terrestrial and underwater communications due to its robustness to jamming, low probability of interception and facility in communication networking. In particular, estimating and tracking the parameters of FH signals are important tasks in underwater acoustic warfare. This paper applies gridless SPICE (GLS) to the parameter estimation of underwater acoustic FH signals, mainly focused on time-frequency pattern and hop timing. As compared to the conventional spectrogram method, the time-frequency analysis method based on gridless SPICE has better frequency acquisition for the same samples. As compared to the SLR method proposed by Daniele Angelosante, this method has better performance for estimating parameters when we do not know the hopping frequency set.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115230830","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 : 1900-01-01DOI: 10.1109/COA.2016.7535723
Song Hao, He Yuan-an, Yang Xiaowei, D. Shang
The flow noise has become an important factor affecting the acoustical stealth performance of AUV in high speed. In the broad sense, all of the radiated noise caused by the instability of the flow field is called flow noise, including the fluid's own noise and noise radiation from flow-induced vibration. Both of the two subclasses of flow-induced noise are investigated in this paper and a precise and efficient numerical method is introduced. With the commercial computational fluid dynamics (CFD) software Fluent and acoustical finite-element method (FEM) software ACTRAN tuned to work jointly with types of preprocessing and post processing software, a computing mechanism combined with large eddy simulation, structural FEM and Lighthill acoustic analogy theory was established. A fluid-structure interaction handling method for shell elements with heavy fluid on both sides was also constructed, which achieves a remarkable reduction on manpower and computational cost on modeling and discrediting the shell structures. A prominent improvement in performance for a flow-induced noise solver on submerged complicated shell structures is also observed. For the validation of our method on both flow-stimulated radiation and flow-induced noise, a number of experiments were conducted on flow-stimulated thin shells and cavity flow-induced noise, consist with the general law of fluid-noise. The method was then applied to the flow-induced noise from a submerged wing-shaped cavity and nozzle, and the pattern of corresponding flow field and sound field further investigated. A corrected reverberation measuring method was also established to overcome the difficulty of flow-noise induced by the noise measurement. Once the spatial mean level of sound pressure in the reverberation control area is measured and corrected, the sound radiation power induced by a submerged complicated source can then be swiftly obtained. The computing method combined with large eddy simulation, structural FEM and Lighthill acoustic analogy theory is further validated by experiments on the flow-induced noise from a submerged wing-shaped cavity in the gravitational water tunnel of an underwater acoustic technique laboratory using our reverberation chamber measuring method. The experimental data fits the simulation solution well.
{"title":"A numerical simulation of flow-induced noise from cavity based on LES and Lighthill acoustic theory","authors":"Song Hao, He Yuan-an, Yang Xiaowei, D. Shang","doi":"10.1109/COA.2016.7535723","DOIUrl":"https://doi.org/10.1109/COA.2016.7535723","url":null,"abstract":"The flow noise has become an important factor affecting the acoustical stealth performance of AUV in high speed. In the broad sense, all of the radiated noise caused by the instability of the flow field is called flow noise, including the fluid's own noise and noise radiation from flow-induced vibration. Both of the two subclasses of flow-induced noise are investigated in this paper and a precise and efficient numerical method is introduced. With the commercial computational fluid dynamics (CFD) software Fluent and acoustical finite-element method (FEM) software ACTRAN tuned to work jointly with types of preprocessing and post processing software, a computing mechanism combined with large eddy simulation, structural FEM and Lighthill acoustic analogy theory was established. A fluid-structure interaction handling method for shell elements with heavy fluid on both sides was also constructed, which achieves a remarkable reduction on manpower and computational cost on modeling and discrediting the shell structures. A prominent improvement in performance for a flow-induced noise solver on submerged complicated shell structures is also observed. For the validation of our method on both flow-stimulated radiation and flow-induced noise, a number of experiments were conducted on flow-stimulated thin shells and cavity flow-induced noise, consist with the general law of fluid-noise. The method was then applied to the flow-induced noise from a submerged wing-shaped cavity and nozzle, and the pattern of corresponding flow field and sound field further investigated. A corrected reverberation measuring method was also established to overcome the difficulty of flow-noise induced by the noise measurement. Once the spatial mean level of sound pressure in the reverberation control area is measured and corrected, the sound radiation power induced by a submerged complicated source can then be swiftly obtained. The computing method combined with large eddy simulation, structural FEM and Lighthill acoustic analogy theory is further validated by experiments on the flow-induced noise from a submerged wing-shaped cavity in the gravitational water tunnel of an underwater acoustic technique laboratory using our reverberation chamber measuring method. The experimental data fits the simulation solution well.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127830694","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 : 1900-01-01DOI: 10.1109/COA.2016.7535815
Yin Jingwei, Duan Pengyu, Zhu Guangping, Chen Wenjian, Liu Qiang
More and more scientific investigations and research activities have been carried out in arctic region, among which the related research on the Arctic Ocean is particularly important. It can be seen that arctic hydro acoustics is the significant support to guarantee military presence and normal scientific research activities. Under-ice acoustic communication experimental was done in Songhua River, Harbin, China in January 2015. Minus 20~30 degrees work environment brings a great challenge to the under-ice experimental campaign. All of the under-ice acoustic communication tests achieve low bit error rate communication at 1km range with different received depth because of the relatively stable under-ice channel. It is found that the closer to the ice the simpler the under-ice acoustic (UIA) channel structure is. Time reversal mirror (TRM) can use the physical characteristics of the UIA channel to focus toward the desired user in multi-user UIA communication. Active average sound intensity (AASI) detector can estimate all azimuths of users with the same frequency band at the same time in order to achieve directional communication by vector combination. Space-division multiple-access (SDMA) based on TRM and AASI detector is used in code-division multiple-access (CDMA) UIA communication to increase the capacity of multiuser system. A method developed for direct sequence spread spectrum communications in an underwater channel are used to extract the transmitted symbols. Under-ice data shows that as many as 12 users can be supported simultaneously in CDMA system combined with SDMA technology.
{"title":"Under-ice CDMA multiuser acoustic communications","authors":"Yin Jingwei, Duan Pengyu, Zhu Guangping, Chen Wenjian, Liu Qiang","doi":"10.1109/COA.2016.7535815","DOIUrl":"https://doi.org/10.1109/COA.2016.7535815","url":null,"abstract":"More and more scientific investigations and research activities have been carried out in arctic region, among which the related research on the Arctic Ocean is particularly important. It can be seen that arctic hydro acoustics is the significant support to guarantee military presence and normal scientific research activities. Under-ice acoustic communication experimental was done in Songhua River, Harbin, China in January 2015. Minus 20~30 degrees work environment brings a great challenge to the under-ice experimental campaign. All of the under-ice acoustic communication tests achieve low bit error rate communication at 1km range with different received depth because of the relatively stable under-ice channel. It is found that the closer to the ice the simpler the under-ice acoustic (UIA) channel structure is. Time reversal mirror (TRM) can use the physical characteristics of the UIA channel to focus toward the desired user in multi-user UIA communication. Active average sound intensity (AASI) detector can estimate all azimuths of users with the same frequency band at the same time in order to achieve directional communication by vector combination. Space-division multiple-access (SDMA) based on TRM and AASI detector is used in code-division multiple-access (CDMA) UIA communication to increase the capacity of multiuser system. A method developed for direct sequence spread spectrum communications in an underwater channel are used to extract the transmitted symbols. Under-ice data shows that as many as 12 users can be supported simultaneously in CDMA system combined with SDMA technology.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125589464","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 : 1900-01-01DOI: 10.1109/COA.2016.7535713
Zhang Zhaohui, Hu Chen, Peng Yuan, Zhang Fengzhen, Mu Lin
Underwater target recognition is very difficult because of the complexity of the ocean environment. The existing recognition technologies are mostly based on time domain, frequency domain, and time-frequency domain. Beam forming technology is a method of target recognition that has been researched and has developed rapidly in recent years. This paper applies beam forming and spatial spectrum analysis technology to an underwater echo signal in order to capture target echo and highlight spot and dimension features in the time-space domain. Image processing is used to extract the dimension and experimental data also verifies the feasibility of this method of beam forming.
{"title":"Target spatial feature abstraction basing on beam forming","authors":"Zhang Zhaohui, Hu Chen, Peng Yuan, Zhang Fengzhen, Mu Lin","doi":"10.1109/COA.2016.7535713","DOIUrl":"https://doi.org/10.1109/COA.2016.7535713","url":null,"abstract":"Underwater target recognition is very difficult because of the complexity of the ocean environment. The existing recognition technologies are mostly based on time domain, frequency domain, and time-frequency domain. Beam forming technology is a method of target recognition that has been researched and has developed rapidly in recent years. This paper applies beam forming and spatial spectrum analysis technology to an underwater echo signal in order to capture target echo and highlight spot and dimension features in the time-space domain. Image processing is used to extract the dimension and experimental data also verifies the feasibility of this method of beam forming.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124701926","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 : 1900-01-01DOI: 10.1109/COA.2016.7535708
Jianjun Zhu, Yukuo Wei, Haisen S. Li, Jingxin Ma
The traditional signal processing method of chirp sub-bottom profiling is a type of matched filtering and is an optimal detector when there is no Doppler shift. Fractional Fourier transform (FrFT) is a linear transformation whose orthogonal basis is a linear frequency modulation signal, so there is no cross term interference when processing multiple or multipath chirp signals. The central characteristic of FrFT is that it has a similar theoretical basis to pulse compression, which makes it possible to use FrFT in the signal processing of chirp sub-bottom profiling. In this paper, the basic principle and theory of chirp sub-bottom profiler signal processing based on FrFT is introduced in detail. Firstly, orthogonal transform is performed to obtain the corresponding analytical form of the echo signal, then the time domain signal is transformed to a fractional Fourier domain (u domain) by optimal FrFT, and the signal enhancement is done using the u domain shading method. Finally, time dimensional transform is used to get the time domain envelope signal of the enhanced sediment impulse response. Time dimensional transform is realized by sample sequence mapping, time offset compensation, extraction and low pass filtering. This process can transform a u domain signal to the time domain directly without complex calculations. Performance comparison of this method to matched filtering is given too, and recommendations for future work are presented.
{"title":"Chirp sub-bottom profiler signal processing method based on fractional Fourier transform","authors":"Jianjun Zhu, Yukuo Wei, Haisen S. Li, Jingxin Ma","doi":"10.1109/COA.2016.7535708","DOIUrl":"https://doi.org/10.1109/COA.2016.7535708","url":null,"abstract":"The traditional signal processing method of chirp sub-bottom profiling is a type of matched filtering and is an optimal detector when there is no Doppler shift. Fractional Fourier transform (FrFT) is a linear transformation whose orthogonal basis is a linear frequency modulation signal, so there is no cross term interference when processing multiple or multipath chirp signals. The central characteristic of FrFT is that it has a similar theoretical basis to pulse compression, which makes it possible to use FrFT in the signal processing of chirp sub-bottom profiling. In this paper, the basic principle and theory of chirp sub-bottom profiler signal processing based on FrFT is introduced in detail. Firstly, orthogonal transform is performed to obtain the corresponding analytical form of the echo signal, then the time domain signal is transformed to a fractional Fourier domain (u domain) by optimal FrFT, and the signal enhancement is done using the u domain shading method. Finally, time dimensional transform is used to get the time domain envelope signal of the enhanced sediment impulse response. Time dimensional transform is realized by sample sequence mapping, time offset compensation, extraction and low pass filtering. This process can transform a u domain signal to the time domain directly without complex calculations. Performance comparison of this method to matched filtering is given too, and recommendations for future work are presented.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120952322","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 : 1900-01-01DOI: 10.1109/COA.2016.7535720
Yongheng Wang, Sun Da-jun, W. Fan, Youwen Zhang
Precise time synchronization is a foundation in the distributed wireless sensor networks in order to ensure the effective co-operation of work such as data fusion and time division scheduling. Due to the high latency caused by low sound speed and mobility between nodes in the underwater acoustic environment, it is difficult to apply mature radio time synchronization algorithms which are widely used in terrestrial networks in the underwater acoustic communication networks. In recent years, several time synchronization algorithms for underwater sensor networks have been developed. However, these algorithms are mostly in the stage of simulation research, which is based on the premise of relative static nodes which require large energy for data exchange and complex linear regression calculations. When taking the mobile platform as the time reference node, the time synchronization between nodes will lead to the problem of bidirectional delay inequality. To tackle these problems, a dynamic time synchronization algorithm based on relative speed compensation with lower energy consumption and higher reliability is proposed. Firstly, an high accuracy clock with low energy consumption is taken in the proposed algorithm to avoid the high energy consumption and large computation in the estimation processing of the clock frequency skew. Secondly, the Linear Frequency Modulation (LFM) pulse pair which can estimate the relative speed of motion is inserted during the exchanging of time information, which can estimate the link propagation delay. Thirdly, a decision mechanism with three times information interaction between two nodes is used to ensure the robustness of time synchronization. Finally, the lake experimental results show that the maximum time synchronization deviation of traditional TSHL algorithm is 18ms, whereas the maximum time synchronization deviation of the proposed algorithm is less than 6ms, and it has higher reliability when the relative speed is up to 6kt between the two nodes.
{"title":"Low consumption dynamic time synchronization for mobile and high latency underwater acoustic communication networks","authors":"Yongheng Wang, Sun Da-jun, W. Fan, Youwen Zhang","doi":"10.1109/COA.2016.7535720","DOIUrl":"https://doi.org/10.1109/COA.2016.7535720","url":null,"abstract":"Precise time synchronization is a foundation in the distributed wireless sensor networks in order to ensure the effective co-operation of work such as data fusion and time division scheduling. Due to the high latency caused by low sound speed and mobility between nodes in the underwater acoustic environment, it is difficult to apply mature radio time synchronization algorithms which are widely used in terrestrial networks in the underwater acoustic communication networks. In recent years, several time synchronization algorithms for underwater sensor networks have been developed. However, these algorithms are mostly in the stage of simulation research, which is based on the premise of relative static nodes which require large energy for data exchange and complex linear regression calculations. When taking the mobile platform as the time reference node, the time synchronization between nodes will lead to the problem of bidirectional delay inequality. To tackle these problems, a dynamic time synchronization algorithm based on relative speed compensation with lower energy consumption and higher reliability is proposed. Firstly, an high accuracy clock with low energy consumption is taken in the proposed algorithm to avoid the high energy consumption and large computation in the estimation processing of the clock frequency skew. Secondly, the Linear Frequency Modulation (LFM) pulse pair which can estimate the relative speed of motion is inserted during the exchanging of time information, which can estimate the link propagation delay. Thirdly, a decision mechanism with three times information interaction between two nodes is used to ensure the robustness of time synchronization. Finally, the lake experimental results show that the maximum time synchronization deviation of traditional TSHL algorithm is 18ms, whereas the maximum time synchronization deviation of the proposed algorithm is less than 6ms, and it has higher reliability when the relative speed is up to 6kt between the two nodes.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130074439","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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