Develop an Adaptive Real-Time Indoor Intrusion Detection System Based on Empirical Analysis of OFDM Subcarriers

Zhuang, Wei; Shen, Yixian; Li, Lü; Gao, Chunming; Ding, Dong

doi:10.3390/s21072287

Cited by 9 publications

(4 citation statements)

References 53 publications

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“…In the process of signal transmission [17,18], due to the complex underwater environment, [19] most images contain noise. In order to verify the feasibility of the algorithm, it is necessary to apply noise to the sample images [20] according to the actual underwater noise.…”

Section: Model Of Noise Imagesmentioning

confidence: 99%

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

Mao¹,

Yan²,

Liu³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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It has remained a hard nut for years to segment sonar images of jacket installation environment, most of which are noisy images with inevitable blur after noise reduction. For the purpose of solutions to this problem, a fast segmentation algorithm is proposed on the basis of the gray value characteristics of sonar images. This algorithm is endowed with the advantage in no need of segmentation thresholds. To realize this goal, we follow the undermentioned steps: first, calculate the gray matrix of the fuzzy image background. After adjusting the gray value, the image is divided into three regions: background region, buffer region and target regions. After filtering, we reset the pixels with gray value lower than 255 to binarize images and eliminate most artifacts. Finally, the remaining noise is removed by morphological processing. The simulation results of several sonar images show that the algorithm can segment the fuzzy sonar images quickly and effectively. Thus, the stable and feasible method is testified.

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Section: Model Of Noise Imagesmentioning

confidence: 99%

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

Mao¹,

Yan²,

Liu³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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show abstract

“…Specifically, the peak power corresponds to IEEE 802.11 a/n, IEEE 802.11 g, and IEEE 802.11 b, being 30, 20, and 10 dBm, respectively. It also has 14 channels at 20 MHz per channel, and the signal modulation is OFDM [45][46][47]. LTE 4G/5G is the current mainstream in mobile communications.…”

Section: Ground-based Systemsmentioning

confidence: 99%

A Novel Signal Design and Performance Analysis in NavCom Based on LEO Constellation

Liu

Chen

et al. 2021

Sensors

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The mega-launch of low Earth orbit satellites (LEOs) represents a critical opportunity to integrate navigation and communication (NavCom), but first, challenges related to signal design must be overcome. This article proposes a novel signal scheme named CE-OFDM-PM. Via research on the in-band or adjacent band, it was found that the proposed signal scheme was suitable for S-band and had a wide normalized power spectrum density (PSD), high peak-to-side lobe ratio (PSR), and multiple peaks in autocorrelation. In an analysis of the simulation performance evaluation in navigation and communication, it is found that the proposed signal scheme has the potential for high accuracy, a code tracking accuracy of up to 0.85 m, a small mutual influence between the proposed signal scheme and other schemes, excellent anti-interference properties, and a better performance at both short and long distances in terms of its anti-multipath capability. Furthermore, the proposed signal scheme shows the ability to communicate between satellites and the ground and is outstanding in terms of its bit error rate (BER), CNR, and energy per bit to noise power spectral density ratio (Eb/N0). From the technical, theoretical, and application perspectives, our proposed signal scheme has potential as an alternative scheme in future BDS, PNTs, and even 5G/B5G.

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“…At present, human behavior research based on CSI has achieved good results. Currently, CSI can be used in intrusion detection [15][16][17] with gesture recognition [18][19][20]. Moreover, WiFi devices open new paths for gesture recognition due to their simplicity and ease of deployment.…”

Section: Introductionmentioning

confidence: 99%

Air-CSL: Chinese Sign Language Recognition Based on the Commercial WiFi Devices

Hong-hong

Feng

Hao

et al. 2022

Wireless Communications and Mobile Computing

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Artificial intelligence and Internet of Things (IoT) devices are experiencing explosive growth. Currently, the commonly used gesture recognition methods are difficult to deploy and expensive, so this paper uses the Channel State Information (CSI) for Chinese sign language recognition. Aiming at the problems of current gesture recognition methods, such as strong personnel dependence, high computational resource consumption, and low robustness, we proposed a Chinese sign language gesture recognition method named Air-CSL. In this method, the Local Outlier Factor (LOF) removal algorithm and the Discrete Wavelet Transform (DWT) are used to reduce the noise in the data, and the subcarriers that best represent the gesture data are selected by principal component analysis. After denoising, mathematical statistics were extracted from the gesture waveform as the eigenvalues, and the features were fused by the Deep Restricted Boltzmann Machine (DBM). Finally, the result of gesture classification and recognition is obtained by the Gated Recurrent Unit (GRU). In this way, the prediction model realizes as well as the classification of sign language gestures. The results show that the proposed method can effectively recognize Chinese sign language gestures of different people in different environments and has good robustness.

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Develop an Adaptive Real-Time Indoor Intrusion Detection System Based on Empirical Analysis of OFDM Subcarriers

Cited by 9 publications

References 53 publications

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

A Novel Signal Design and Performance Analysis in NavCom Based on LEO Constellation

Air-CSL: Chinese Sign Language Recognition Based on the Commercial WiFi Devices

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