Non-Uniform Non-Orthogonal Multicarrier Underwater Communication for Compressed Sonar Image Data Transmission

Cui, Junfei; Han, Guangyao; Su, Yishan; Fu, Xiaomei

doi:10.1109/tvt.2021.3103551

Cited by 11 publications

(3 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[2]- [4]. In harsh environments, the collected information of the original image must be effectively compressed [5]. The image information can be transferred to the surface workstation.…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Underwater Image Compression and Reconstruction Based on VQ-VAE-2

Yang,

Fei,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

Due to the low bandwidth of underwater acoustic communication, large-sized color images cannot be transmitted in a timely manner. In response to this problem, this paper uses the deep learning-based VQ-VAE-2 model to propose two other fine-tuning model structures, NVQ and VQI, to encode, compress, transmit, reconstruct and generate large-information original images through convolutional networks. The NVQ model reduces the characteristics of the bottom quantization, and the VQI model re-quantizes the bottom quantization result, which significantly reduces the amount of data transmitted. The picture compression rate of the VQ-VAE-2 model is 13:1, and the picture compression rates of NVQ and VQI are 32:1 and 60:1. SSIM (Structural Similarity) of VQ-VAE-2, NVQ and VQI are 0.94, 0.91 and 0.87, respectively. In contrast to previous work, 1) we obtain visually pleasing reconstructions that are perceptually similar to the input, and 2) our approaches have short encoding time and decoding time, generate character strings directly without adding additional overhead, so have shorter transmission time compared with other methods.

show abstract

“…[2]- [4]. In harsh environments, the collected information of the original image must be effectively compressed [5]. The image information can be transferred to the surface workstation.…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Underwater Image Compression and Reconstruction Based on VQ-VAE-2

Yang,

Fei,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Radio waves are extremely strongly attenuated in saltwater because seawater which contains a tremendous amount of salt is a conductive transmission medium and could significantly attenuate the electromagnetic waves. Acoustic sensors, such as underwater acoustic sensor networks (UASNs) [6], Doppler velocity log (DVL) [7], sonar [8], could also provide effective localization capability, but the high-cost and low-bandwidth hinder their application scenarios. In particular, many breakwaters have been built up near ports, where the magnetic interference is strong, and some acoustic positioning devices like ultra-short baseline (USBL) is prone to fail.…”

Section: Introductionmentioning

confidence: 99%

Robust Real-Time AUV Self-Localization Based on Stereo Vision-Inertia

Wang

et al. 2023

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Autonomous underwater vehicles (AUVs) play an important role in deep-sea exploration, in which AUV selflocalization is a key component. However, due to poor visibility caused by challenging marine environments, AUVs are often equipped with high-cost and heavy-weight acoustic sensors to accomplish localization tasks. We propose a robust real-time AUV self-localization method based on stereo camera and inertial sensor, which merges point and diagonal features, as well as inertial measurements to overcome the challenges of poor visibility. Our method also includes an underwater loop detection algorithm based on the combination of points and diagonal segments, which can extract effective binary descriptors in lowtextured underwater scenarios. Furthermore, we develop an AUV self-localization system based on a real-time, portable, low-cost, and small volume sensor suite. Finally, we test the proposed method in a real underwater environment using our sensor suite, and the experimental results demonstrate the effectiveness of the proposed method under dramatically changing underwater scenarios.

show abstract

“…Underwater acoustic imaging (UAI) has been widely used in underwater object recognition, underwater topographic survey, underwater archaeology, underwater operations and underwater equipment [1]. Compared with underwater optical imaging, UAI has the advantage of further visibility distance because of less acoustic transmission loss [2,3]. Nowadays, UAI becomes more useful in observing, recognizing or classifying underwater objects [4,5].…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging

Teng

Yang

et al. 2022

JMSE

View full text Add to dashboard Cite

Underwater acoustic imaging employs a special form of array which includes numerous transducer elements to achieve beamforming. Although a large-scale array can bring high imaging resolution, it will also cause difficulties in hardware complexity and real-time application. In this paper, in order to reduce the number of array elements, a sparse optimization for Mills cross is proposed, considering the elements’ distributions and weights design. The improved genetic algorithm is adopted to generate evolutions for sparse solution. In order to ensure effective convergence and successful evolution, relevant genetic operators are proposed, including appropriate population coding, correct fitness function, reasonable selection strategy and efficient two-point orthogonal crossover, among others. Essentially, a satisfied sparse solution is a result of mutual restraint between array elements’ survivals and their weights. The simulations reveal that our sparse cross array decreases the number of elements by 8.25% compared to the conventional Mills cross multiplicative array, while keeping the advantages of narrow main lobe width and low sidelobe level. Improved genetic algorithm is an effective method for the underwater acoustic imaging array to implement the sparse optimization.

show abstract

Non-Uniform Non-Orthogonal Multicarrier Underwater Communication for Compressed Sonar Image Data Transmission

Cited by 11 publications

References 46 publications

WITHDRAWN: Underwater Image Compression and Reconstruction Based on VQ-VAE-2

WITHDRAWN: Underwater Image Compression and Reconstruction Based on VQ-VAE-2

Robust Real-Time AUV Self-Localization Based on Stereo Vision-Inertia

Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging

Contact Info

Product

Resources

About