Optimum Filters for the Detection of Signals in Noise

Zadeh, Lotfi A.; Ragazzini, John R.

doi:10.1109/jrproc.1952.274117

Cited by 90 publications

(21 citation statements)

References 11 publications

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“…Dl . However, as ~1 2 becomes appreciable , the amplitude and ph ase shift of the steady-state ALE impulse response begin to change considerably, as is observed in (24) - (26).…”

mentioning

confidence: 75%

Adaptive enhancement of multiple sinusoids in uncorrelated noise

Zeidler¹,

Satorius²,

Chabries³

et al. 1978

IEEE Trans. Acoust., Speech, Signal Process.

189

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“…Dl . However, as ~1 2 becomes appreciable , the amplitude and ph ase shift of the steady-state ALE impulse response begin to change considerably, as is observed in (24) - (26).…”

mentioning

confidence: 75%

Adaptive enhancement of multiple sinusoids in uncorrelated noise

Zeidler¹,

Satorius²,

Chabries³

et al. 1978

IEEE Trans. Acoust., Speech, Signal Process.

189

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“…The 1.5-bit FM demodulator proposed in figure 4 borrows the design of matched-filter [13]; however, their principles are different. In our system, the local signals fed into the multipliers, e j2πf I t and e j2π(f I ±f R )t , do not exactly match any signal transmitted.…”

Section: B the 15-bit Fm Demodulatormentioning

confidence: 99%

Detecting multi-channel wireless microphone user emulation attacks in white space with noise

Zeng

Richardson

et al. 2013

8th International Conference on Cognitive Radio Oriented Wireless Networks

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Abstract-In this work, we study a special kind of primary user emulation (PUE) attack, named wireless microphone user emulation (WMUE) attack in white space cognitive radio networks. In WMUE attacks, a malicious user emulates wireless microphone (WM) signals in order to block secondary users. Existing work on WMUE attack detection deals with single channel senario. Although multi-channel WM (MCWM) systems are common, detecting WMUE attacks under a multi-channel setting in noisy environments has not been well studied and the existing solution for single channel case cannot be directly applied. In a practical multi-channel WM system, the audio signals on different channels mix with each other and are contaminated by noises, which introduce great challenges on WMUE attack detection. We propose a novel multi-channel WMUE attack detection scheme which is based on the crosscorrelation between the demodulated FM signal and the acoustic signal. The audio interferences, audio noises, and RF noises are all resisted by the cross-correlation. To reduce computation complexity, we propose a 1.5-bit FM demodulator whose outputs are represented by only 0, 1 and -1. Moreover, we set up a MCWM system and developped a hardware based prototype to evaluate the performance of the proposed scheme. Experimental results show that, the proposed scheme can effectively detect multi-channel WMUE attacks within 0.25 second with detection rate larger than 0.9 and false alarm rate lower than 0.1 under low signal-to-noise ratios.

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“…The detection of a known deterministic signal in additive Gaussian noise is solved using a correlator or matched filter [45,55,62,12 Part I]. For the case of a random signal in white noise, a two stage process is utilized to first estimate the signal and then correlate this estimate with the received waveform.…”

Section: A Backgroundmentioning

confidence: 99%

A Parametric Detection Approach Using Multichannel Processes

Michels¹

1989

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Optimum Filters for the Detection of Signals in Noise

Cited by 90 publications

References 11 publications

Adaptive enhancement of multiple sinusoids in uncorrelated noise

Adaptive enhancement of multiple sinusoids in uncorrelated noise

Detecting multi-channel wireless microphone user emulation attacks in white space with noise

A Parametric Detection Approach Using Multichannel Processes

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