Digital pseudorandom uniform noise generators for ADC histogram test

Alves, Jose Domingos; Evans, G.

doi:10.1109/dcis.2015.7388592

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Noise can originate from various factors, primarily from prolonged exposure and high sensitivity. Types of noise include Gaussian noise [14]- [16], Salt and Pepper noise [17]- [19], uniform noise [20]- [22], photon noise [23]- [25], readout noise [26]- [28], reset noise [29]- [31], quantization noise [32]- [34], and more [35]- [37]. To mitigate such noise, noise filters are employed.…”

Section: Algorithm For Recognizing Sudden Accelerationmentioning

confidence: 99%

Image and noise reduction for assessing driver incompetence in cases of sudden unintended acceleration

Rhee,

Cho

2024

IJEECS

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<span>This paper explores using cameras aimed at the accelerator and brake pedals during sudden unintended acceleration in cars, removing noise from captured images to determine driver incompetence. A car model was constructed using Raspberry Pi to simulate brake malfunction using random functions, increasing the revolutions per minute (RPM) to simulate sudden acceleration. By employing a DC encoder motor to measure the motor's rotational speed through waveform counts, the RPM was calculated. The study recognized sudden acceleration when the brake malfunctioned through the DC encoder motor, causing an abnormal RPM increase, allowing camera capture toward the accelerator and brake during sudden acceleration events. Precautions were taken for problems arising from noise in captured images. The Unix operating system was utilized to apply Gaussian filter image processing techniques for noise removal. While using an average value filter led to abrupt changes by replacing with the average of surrounding signals, resulting in an unsmooth image, a Gaussian filter was used in this study to decrease weights as distance from the center increased, mitigating these issues.</span>

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Section: Algorithm For Recognizing Sudden Accelerationmentioning

confidence: 99%

Image and noise reduction for assessing driver incompetence in cases of sudden unintended acceleration

Rhee,

Cho

2024

IJEECS

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“…In this context, the profiling function was supposed to exploit designations coming from a surveillance radar, included in the same defense system. The proposed technique, based on the linear feedback shift register (LFSR) theory [19], is less effective than some modern PN number generators (e.g., [20,21]) but it is particularly suited for our purpose because of the good compromise between its performances and its computational burden. The reference can be directly reproduced in reception and the appropriate delay with respect to the received echo signal can be set using the LFSR initial seed in case of a raw designation.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Processing Architecture for Range Profiling Using Noise Radar Technology

2018

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Abstract:The importance of high resolution range profiles (HRRPs) for radar applications like tracking or classification is well known. In the scientific literature several approaches have been investigated to obtain HRRPs from wideband radar signals. Recent works show that noise radar waveforms can be exploited in this sense due to their high resolution and low peak to sidelobe ratio (PSLR) properties. However their use can cause some issues in applications where long time integrations are required, e.g., in the presence of a low effective radiated power (ERP) transmitter: recording the reference signal in this case would be difficult due to the big quantity of data. This work proposes a real time digital processing schematic based on linear feedback shift registers (LFSRs) which is very flexible and has a low computational burden: its internal state can be easily controlled and reproduced in reception, where a multichannel correlator is exploited as matched filter. The resulting signal, compared to typical "pulse compression" and noise radar waveforms, shows similar performances but a lower order of complexity in terms of real time generation and reception.

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Digital pseudorandom uniform noise generators for ADC histogram test

Cited by 2 publications

References 33 publications

Image and noise reduction for assessing driver incompetence in cases of sudden unintended acceleration

Image and noise reduction for assessing driver incompetence in cases of sudden unintended acceleration

An Efficient Processing Architecture for Range Profiling Using Noise Radar Technology

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