Benutzer:Lonski/Sensor array - Versionsgeschichte

TenWhile6: Importartikel [AdminHelper]

2025-02-14T20:35:26Z

Importartikel [AdminHelper]

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			{{Importartikel}}
	{{Short description\|Group of sensors used to increase gain or dimensionality over a single sensor}}		{{Short description\|Group of sensors used to increase gain or dimensionality over a single sensor}}
	{{Multiple issues\|		{{Multiple issues\|
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	{{DEFAULTSORT:Sensor Array}}		{{DEFAULTSORT:Sensor Array}}
	[[Category:Sensors]]		<!--[[Category:Sensors]]-->

TenWhile6: 241 Versionen von :en:Sensor_array importiert: WP:IMP * Special:Diff/253330600 * user:Lonski

2025-02-14T20:31:18Z

241 Versionen von en:Sensor_array importiert: WP:IMP * Special:Diff/253330600 * user:Lonski

← Nächstältere Version	Version vom 14. Februar 2025, 22:31 Uhr
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en>Kku: /* MVDR (Capon) beamformer */ cite

2024-01-09T16:20:49Z

MVDR (Capon) beamformer: cite

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	=== MVDR (Capon) beamformer ===		=== MVDR (Capon) beamformer ===

	The Minimum Variance Distortionless Response beamformer, also known as the Capon beamforming algorithm,<ref>J. Capon, ~~“High–Resolution~~ ~~Frequency–Wavenumber~~ ~~Spectrum~~ ~~Analysis,”~~ Proceedings of the IEEE, 1969~~, Vol.~~ 57, ~~pp.~~ 1408–1418</ref> has a power given by		The Minimum Variance Distortionless Response beamformer, also known as the Capon beamforming algorithm,<ref>{{cite journal \|last1=Capon \|first1=J. \|title=High-resolution frequency-wavenumber spectrum analysis \|journal=Proceedings of the IEEE \|date=1969 \|volume=57 \|issue=8 \|pages=1408–1418 \|doi=10.1109/PROC.1969.7278}}</ref> has a power given by

	<math> \hat{P}_{Capon}(\theta)=\frac{1}{\boldsymbol v^H \boldsymbol R^{-1} \boldsymbol v} \ \ (6) </math>.		<math> \hat{P}_{Capon}(\theta)=\frac{1}{\boldsymbol v^H \boldsymbol R^{-1} \boldsymbol v} \ \ (6) </math>.

en>Kku: /* Further reading */ cite

2024-01-09T16:18:57Z

en>Kku: /* Other arrays */ Image sensor

2024-01-08T18:10:00Z

Other arrays: Image sensor

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	*[[Geophone\|Geophone array]] used in [[Reflection seismology]]		*[[Geophone\|Geophone array]] used in [[Reflection seismology]]
	*[[Towed array sonar\|Sonar array]] is an array of hydrophones used in underwater imaging		*[[Towed array sonar\|Sonar array]] is an array of hydrophones used in underwater imaging
			*[[Image sensor]]s for digital cameras

	== Delay-and-sum beamforming ==		== Delay-and-sum beamforming ==

en>Kku: /* Further reading */ cite

2024-01-08T18:08:16Z

en>Cargonat: /* Antenna array */ Added link for FFT (fast Fourier Transform)

2023-04-15T10:33:41Z

Antenna array: Added link for FFT (fast Fourier Transform)

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	*[[Phased array]], An antenna array where the phase shifts (and amplitudes) applied to the elements are modified electronically, typically in order to steer the antenna system's directional pattern, without the use of moving parts		*[[Phased array]], An antenna array where the phase shifts (and amplitudes) applied to the elements are modified electronically, typically in order to steer the antenna system's directional pattern, without the use of moving parts
	*[[Smart antenna]], a phased array in which a signal processor computes phase shifts to optimize reception and/or transmission to a receiver on the fly, such as is performed by cellular telephone towers		*[[Smart antenna]], a phased array in which a signal processor computes phase shifts to optimize reception and/or transmission to a receiver on the fly, such as is performed by cellular telephone towers
	*[[Digital antenna array]], this is [[smart antenna]] with multi channels ''digital beamforming'', usually by using FFT.		*[[Digital antenna array]], this is [[smart antenna]] with multi channels ''digital beamforming'', usually by using [[Fast Fourier transform\|FFT]].
	*[[Interferometry\|Interferometric array]] of radio telescopes or optical telescopes, used to achieve high resolution through interferometric correlation		*[[Interferometry\|Interferometric array]] of radio telescopes or optical telescopes, used to achieve high resolution through interferometric correlation
	*[[Direction finding#Watson-Watt .2F Adcock antenna array\|Watson-Watt / Adcock antenna array]], using the Watson-Watt technique whereby two Adcock antenna pairs are used to perform an amplitude comparison on the incoming signal		*[[Direction finding#Watson-Watt .2F Adcock antenna array\|Watson-Watt / Adcock antenna array]], using the Watson-Watt technique whereby two Adcock antenna pairs are used to perform an amplitude comparison on the incoming signal

en>Pbsouthwood: Adding local short description: "Group of sensors used to increase gain or dimensionality over a single sensor", overriding Wikidata description "group of sensors, usually deployed in a geometric pattern, used to increase gain or dimensionality over a single sensor"

2023-01-14T09:46:23Z

Adding local short description: "Group of sensors used to increase gain or dimensionality over a single sensor", overriding Wikidata description "group of sensors, usually deployed in a geometric pattern, used to increase gain or dimensionality over a single sensor"

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			{{Short description\|Group of sensors used to increase gain or dimensionality over a single sensor}}
	{{Multiple issues\|		{{Multiple issues\|
	{{more citations needed\|date=January 2015}}		{{more citations needed\|date=January 2015}}

92.27.156.1: /* Plane wave, time domain beamforming */

2022-12-05T14:33:35Z

Plane wave, time domain beamforming

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	Each sensor is associated with a different delay. The delays are small but not trivial. In frequency domain, they are displayed as phase shift among the signals received by the sensors. The delays are closely related to the incident angle and the geometry of the sensor array. Given the geometry of the array, the delays or phase differences can be used to estimate the incident angle. Eq. (1) is the mathematical basis behind array signal processing. Simply summing the signals received by the sensors and calculating the mean value give the result		Each sensor is associated with a different delay. The delays are small but not trivial. In frequency domain, they are displayed as phase shift among the signals received by the sensors. The delays are closely related to the incident angle and the geometry of the sensor array. Given the geometry of the array, the delays or phase differences can be used to estimate the incident angle. Eq. (1) is the mathematical basis behind array signal processing. Simply summing the signals received by the sensors and calculating the mean value give the result

	<math>y = \frac{1}{M}\sum_{i=1}^{M} \boldsymbol x_i (t-\Delta t_i) </math> .		<math>y = \frac{1}{M}\sum_{i=1}^{M} \boldsymbol x_i (t-\Delta t_i) \ \ (2) </math> .

	Because the received signals are out of phase, this mean value does not give an enhanced signal compared with the original source. Heuristically, if we can find delays of each of the received signals and remove them prior to the summation, the mean value		Because the received signals are out of phase, this mean value does not give an enhanced signal compared with the original source. Heuristically, if we can find delays of each of the received signals and remove them prior to the summation, the mean value

	<math>y = \frac{1}{M}\sum_{i=1}^{M} \boldsymbol x_i (t) </math>		<math>y = \frac{1}{M}\sum_{i=1}^{M} \boldsymbol x_i (t) \ \ (3) </math>

	will result in an enhanced signal. The process of time-shifting signals using a well selected set of delays for each channel of the sensor array so that the signal is added constructively is called '''[[beamforming]]'''.		will result in an enhanced signal. The process of time-shifting signals using a well selected set of delays for each channel of the sensor array so that the signal is added constructively is called '''[[beamforming]]'''.

195.220.58.236: /* Plane wave, time domain beamforming */

2022-05-23T15:51:34Z

Plane wave, time domain beamforming

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	will result in an enhanced signal. The process of time-shifting signals using a well selected set of delays for each channel of the sensor array so that the signal is added constructively is called '''[[beamforming]]'''.		will result in an enhanced signal. The process of time-shifting signals using a well selected set of delays for each channel of the sensor array so that the signal is added constructively is called '''[[beamforming]]'''.
	In addition to the delay-and-sum approach described above, a number of spectral based (non-parametric) approaches and parametric approaches exist which improve various performance metrics. These beamforming algorithms are briefly described as ~~follow~~		In addition to the delay-and-sum approach described above, a number of spectral based (non-parametric) approaches and parametric approaches exist which improve various performance metrics. These beamforming algorithms are briefly described as follows
	.		.

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	==Further reading==		==Further reading==
	* ~~H. L.~~ Van Trees, ~~“Optimum~~ ~~array~~ ~~processing – Part IV of detection~~, estimation, and modulation ~~theory”,~~ ~~John~~ Wiley, ~~2002~~		*{{cite book \|last1=Van Trees \|first1=Harry L. \|title=Detection, estimation, and modulation theory. 4: Optimum array processing \|date=2002 \|publisher=Wiley \|location=New York, NY \|isbn=9780471093909\|doi=10.1002/0471221104}}
	* H. Krim and M. Viberg, “Two decades of array signal processing research”, IEEE Transactions on Signal Processing Magazine, July 1996		* H. Krim and M. Viberg, “Two decades of array signal processing research”, IEEE Transactions on Signal Processing Magazine, July 1996
	* S. Haykin, Ed., “Array Signal Processing”, Eaglewood Cliffs, NJ: Prentice-Hall, 1985		* S. Haykin, Ed., “Array Signal Processing”, Eaglewood Cliffs, NJ: Prentice-Hall, 1985

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	* B. Ottersten, M. Verberg, P. Stoica, and A. Nehorai, “Exact and large sample maximum likelihood techniques for parameter estimation and detection in array processing”, Radar Array Processing, Springer-Verlag, Berlin, pp. 99–151, 1993		* B. Ottersten, M. Verberg, P. Stoica, and A. Nehorai, “Exact and large sample maximum likelihood techniques for parameter estimation and detection in array processing”, Radar Array Processing, Springer-Verlag, Berlin, pp. 99–151, 1993
	* M. Viberg, B. Ottersten, and T. Kailath, “Detection and estimation in sensor arrays using weighted subspace fitting”, IEEE Transactions on Signal Processing, vol. SP-39, pp 2346–2449, November 1991		* M. Viberg, B. Ottersten, and T. Kailath, “Detection and estimation in sensor arrays using weighted subspace fitting”, IEEE Transactions on Signal Processing, vol. SP-39, pp 2346–2449, November 1991
	* M. ~~Feder and~~ E. ~~Weinstein, “Parameter~~ estimation of superimposed signals using the EM ~~algorithm”,~~ IEEE Transactions on ~~Acoustic~~, Speech and Signal ~~Proceeding,~~ ~~vol~~ ~~ASSP-~~36, ~~pp. 447–489,~~ ~~April~~ ~~1988~~		*{{cite journal \|last1=Feder \|first1=M. \|last2=Weinstein \|first2=E. \|title=Parameter estimation of superimposed signals using the EM algorithm \|journal=IEEE Transactions on Acoustics, Speech, and Signal Processing \|date=April 1988 \|volume=36 \|issue=4 \|pages=477–489 \|doi=10.1109/29.1552}}
	* Y. Bresler and Macovski, “Exact maximum likelihood parameter estimation of superimposed exponential signals in noise”, IEEE Transactions on Acoustic, Speech and Signal Proceeding, vol ASSP-34, pp. 1081–1089, October 1986		* Y. Bresler and Macovski, “Exact maximum likelihood parameter estimation of superimposed exponential signals in noise”, IEEE Transactions on Acoustic, Speech and Signal Proceeding, vol ASSP-34, pp. 1081–1089, October 1986
	* R. O. Schmidt, “New mathematical tools in direction finding and spectral analysis”, Proceedings of SPIE 27th Annual Symposium, San Diego, California, August 1983		* R. O. Schmidt, “New mathematical tools in direction finding and spectral analysis”, Proceedings of SPIE 27th Annual Symposium, San Diego, California, August 1983

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			{{Short description\|Group of sensors used to increase gain or dimensionality over a single sensor}}
	{{Multiple issues\|		{{Multiple issues\|
	{{more citations needed\|date=January 2015}}		{{more citations needed\|date=January 2015}}