Barry D. Van Veen and Kevin M. Buckley, "Beamforming - a versatile approach to spatial filtering," IEEE Acoustics, Speech and Signal Processing Magazine, pp. 4--24, April 1988.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....beamforming. In this section we present the array response vectors for both linear and circular arrays. 3.4.4. 1 Array Response Vector for a Linear Array The relative phase of a signal at k being received at the ith element of a linear array of NA elements is given by Van Veen and Buckley in [49]. 51 a = 6 6 6 6 6 6 6 6 6 6 6 6 j cos( k ) j2 cos( k ) j(N A Gamma1) cos( k ) 7 7 7 7 7 7 7 7 7 7 7 7 (3.52) 3.4.4.2 Array Response Vector for a Circular Array The array response vector of a circular array is considerably more complicated to derive ....

....reference mobile power, k = 1) we substitute (4.30) into (4.32) 1 fi ki fi kj cos( i Gamma ff ki Gamma 2f c k ) Gamma ( j Gamma ff kj Gamma 2f c k ) 4.33) 1 fi ki fi kj cos( i Gamma ff ki ) Gamma ( j Gamma ff kj ) 4. 34) Using maximum SNR beamforming [49] for the reference mobile (k = 1) the relative phase of the i element of the array response vector, ff 1i , will equal the relative phase of the i beamforming weight, i . Therefore, cos( i Gamma ff 1i ) Gamma ( j Gamma ff 1j ) cos(0) 1, and (4.34) becomes P 1 = 1 fi 1i ....

[Article contains additional citation context not shown here]

Barry D. Van Veen and Kevin M. Buckley. "Beamforming: A versatile approach to spatial filtering". IEEE ASSP Magazine, pages 4--24, April 1988.

....not converge for the frequency bands where there are overlapping partials, due to the fact that the sources are not statistically independent. 2.3. Spatial separation There exist some methods that exploits the physical locations of the sources in order to separate them, like e.g. beamforming [18]. Recently, the DUET method for separating sources in the timefrequency domain based on spatial cues was introduced in [19] It is fast, simple and still performs quite well for music signals. In the following we are explaining this method in more detail. The method takes a stereo recording of the ....

Barry D. Van Veen and Kevin M. Buckley, "Beamforming - a versatile approach to spatial filtering," IEEE Acoustics, Speech and Signal Processing Magazine, pp. 4--24, 1988.

....is reduced by this method, the range of one access point is increased. Early contributions in the area of antenna arrays for mobile communication are [AMVW91] and [SBEM90] The issue of smart antennas has been overviewed in e.g. God97a, God97b] The special area of beamforming is summarized in [VB88] 3.3.1 Sensor Array Processing To be able to utilize the spatial dimension of the wireless channel, knowledge about the channel is important. Either parametric methods are used to estimate an angle, or statistic methods are used to estimate channel statistics, we need sensor array processing. ....

....to the desired user, the signals transmitted or received on the di#erent antennas elements may be combined to give required gain on the desired signal. In uplink beamforming it possible to estimate the channel via the received signal and thus to have a good channel estimate [God97a, God97b, VB88] The basic method is beamforming, where the weights in the receiver are matched to the estimated channel vector. Zero forcing methods may be used in order to take care of interfering signals, though with high sensitivity of estimation errors and risk of worsening the noise situation. A optimal ....

Barry D. Van Veen and Kevin M. Buckley. Beamforming - a versatile approach to spatial filtering. IEEE Acoustics, Speech, and Signal Processing Magazine, pages 4--24, April 1988.

....S 0090 6778(99)07795 8. 1 This concept is also known as spatial division multiple access or SDMA. This will cause severe cochannel interference (CCI) at the receiver. Antenna arrays are then indispensable tools for separating the signals from different users. With an antenna array, beamforming [1] can be used to suppress CCI. However, in situations with frequency selective fading, beamformers that operate only in the spatial domain can suppress only a few interferers. In this paper, we illustrate, compare, and explore two more elaborate ways of using an antenna array at the receiver to ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A versatile approach to spatial filtering," IEEE ASSP Mag., vol. 5, pp. 4--24, Apr. 1988.

....into sectors. The transformation matrices used in each sector for the dimension reduction to beamspace can be designed according to [1, 2] or according to some of the other ways proposed in the literature as, e.g. 11, 12, 13] See also the references in the survey article on beamforming in [14]. It is here desirable to have some robustness (w.r.t bias, e.g. against out of sector emitters, since it is not likely that all emitters will be in the same sector. This desirable property is an issue that requires further study, however. See [15] for an approach involving numerical ....

B.D. Van Veen and K.M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering", IEEE ASSP Magazine, pages 4--24, April 1988.

....from electrical activity in a limited area in the brain. During epileptic seizures, the EEG often shows rhythmic electrical activity arising from the same epileptogenic area in the brain. Beamforming is a technique that performs a spatial filtering of signals measured at discrete sensors [3]. Beamformers calculate a linear combination of the time sequences measured at the di#erent sensors, with the aim of preserving the signal components originating from a desired direction or location, while at the same time suppressing interference from other directions or locations. A typical ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A versatile approach to spatial filtering," IEEE Acoustics, Speech and Signal Processing Magazine, vol. 5, pp. 4--24, 1988.

....to fuse data collected at several sensors in order to facilitate the task at hand, be it signal detection estimation, source separation, or source localization. The long lasting interest in this area can be traced to the large number of applications where data is collected in both space and time [1]. In this paper, we will focus on the ability of measurements taken from an array of receiving sensors to enhance signal estimation. A gain in the signal power over the noise variance is achieved through beamforming, which can be performed via partially coherent, coherent, or noncoherent combining ....

B. Van Veen and K. Buckle, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE Signal Processing Magazine, April 1998.

....(DOA) estimation and beamforming for electromagnetic (EM) waves are two common objectives of array processing. Early work on DOA estimation and beamforming has been based on scalar sensors, each of which provides measurements of only one component of the electric or magnetic field induced [18]. Subsequent research has investigated the use of sensors that measure two components of the electric or magnetic field (see, e.g. 19] 21] and tripole sensors that measure three complete components of the electric field [22] In recent years, researchers have proposed the use of EM vector ....

....if the interference is CP (i.e. then SINR attains SINR , which is the value when there is no interference, regardless of the DOA separation and the interference s power. A. Comparisons with Scalar Sensor Arrays Beamformers using scalar sensor arrays have been addressed in the literature [18]. Here, we shall discuss some advantages of using an EM vector sensor as compared with scalar sensor arrays for beamforming in 3 D space. First, for a scalar sensor array, at least three sensors are needed to perform beamforming, which means that it will occupy a larger space than an EM vector ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A versatile approach to spatial filtering," IEEE Acoust. Speech, Signal Processing Mag., vol. 5, pp. 4--24, Apr. 1988.

....algorithms in the uplink is given in [6] Another way of reducing the interference between users is to sectorize the cells using directional antennas. While this approach still utilizes the spatial domain to introduce orthogonalization to the system, it is fundamentally di#erent than beamforming [12, 13]. Beamforming combines the received signals from multiple antennas in a unique way for each user to suppress the interference that user sees. Sectorization merely employs directional antennas and each user s signal is received at only one of these antennas. Since only a subset of the users are ....

B. D. Van Veen and K. M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE Acoustic, Speech and Signal Processing Magazine, pages 4--24, April 1988.

....expected squared error between the transmitted signal and the output of the receiver filter. It is also the linear filter which maximizes the output SIR [13] Exploiting spatial diversity through the use of array combining to increase the system capacity is a familiar notion in wireless systems [14]. For narrowband systems, it was shown that multiple antennas can be used to null out interferers and achieve diversity gain [15] Increasing the capacity of CDMA systems by employing antenna arrays at the base station has been proposed in [16] The idea is to combine the outputs of multiple ....

B. D. Van Veen and K. M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE Acoustic, Speech and Signal Processing Magazine, pages 4--24, April 1988.

....and are based on other performance measure such as Signal to Noise Ratio (SNR) performance measure Maximum Noise Variance (MNV) performance measure However, for conventional methods, the solutions are all basically the same. For a more detailed review of such beamforming methods refer to [31]. The conventional methods obtain V as the spatial analogue of the classical periodogram in temporal time series analysis. The classical periodogram suffers from the fact, that its standard deviation is approximately as large as the quantity to be estimated. Therefore in general it can be said, ....

Barry D. Van Veen and Kevin M. Buckley. Beamforming : A versatile approach to spatial filtering. IEEE Signal Processing Magazine, pages 4--24, April 1988.

....by the smart antenna system is the estimation of the users directions of arrival (DOAs) On the base of estimated DOAs a suitable radiation pattern of the antenna array is shaped, in order to cancel co channel interference. Due to the strict constraints on the payload use of adaptive beamforming [5] has been investigated. Such a technique can be seen as a spatial ltering operation performed on the digital sampled version of the demodulated signal received by each antenna element. This technique permits to track the user movements, and consequently to reuse the same frequency for users ....

B. D. Van Veen and K. Buckley, \Beamforming: A Versatile Approach to Spatial Filtering", IEEE ASSP Magazine, April 1988

.... Space Frequency Domain Time Domain Sensors per Output Figure 1: Some adaptive sonar beamforming techniques and their performance requirements Beamforming is the technique which spatially filters the signals received from an array of sensors and estimates the spatial features of the sources [27]. A typical sonar beamformer has an array of sensor elements (usually a towed array or a hull mounted array with 20 to 1000 hydrophone elements) It passively receives the acoustic propagation wave field signals and samples the signals. In most cases, the sampling rate is less than 25 KHz. The ....

....the shading for each direction of look. The adaptation of the entire sensor element domain is called fully adaptive processing. Since fully adaptive processing is computationally demanding, partially adaptive processing is, sometimes, used to reduce the dimensionality of adaptive weight matrices [27]. Numerical methods form the basis of the weight adaptation stage. Data decomposition based least squares algorithms are generally employed. These algorithms include QR decomposition (QRD) singular value decomposition (SVD) and Cholesky Factorization, among others. Figure 1 shows the various ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, Apr. 1988, pp. 4-24. 32

....adaptive STAP algorithms into a number of smaller, more manageable adaptive problems while achieving near optimum performance. 2. Sonar Beamforming: Beamforming is a technique which spatially filters the signals received from an array of sensors and estimates the spatial features of the sources [33]. A typical sonar beamformer has an array of sensor elements (usually a towed array or a hull mounted array with 20 to 1000 hydrophone elements) It passively receives the acoustic propagation wave field signals and samples the signals. In most cases, the sampling rate is less than 25 KHz. The ....

....of the shading for each direction of look. The adaptation of the entire sensor element domain is called fully adaptive processing. Since fully adaptive processing is computationally demanding, partially adaptive processing is sometimes used to reduce the dimensionality of adaptive weight matrices [33]. Numerical methods form the basis of the weight adaptation stage. Data decomposition based least squares algorithms are generally employed. These algorithms include QR decomposition (QRD) singular value decomposition (SVD) and Cholesky Factorization, among others. As more advanced numerical ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, Apr. 1988. 50

.... Space Frequency Domain Time Domain Sensors per Output Figure 1: Some adaptive sonar beamforming techniques and their performance requirements Beamforming is the technique which spatially filters the signals received from an array of sensors and estimates the spatial features of the sources [25]. A typical sonar beamformer has an array of sensor elements (usually a towed array or a hull mounted array with 20 to 1000 hydrophone elements) It passively receives the acoustic propagation wave field signals and samples the signals. In most cases, the sampling rate is less than 25 KHz. The ....

....of the shading for each direction oflook. The adaptation of the entire sensor element domain is called fully adaptive processing. Since fully adaptive processing is computationally demanding, partially adaptive processing is used, sometimes, to reduce the dimensionality of adaptive weight matrices [25]. Numerical methods form the basis of the weight adaptation stage. Data decomposition based least squares algorithms are generally employed. These algorithms include QR decomposition (QRD) singular value decomposition (SVD) and Cholesky Factorization, among others. Figure 1 shows the various ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, Apr. 1988.

....structure is compared to a fullband adaptive beamformer, highlighting the bene t of our method. 1. Introduction In beamforming, the task is to steer a sensor array towards a signal impinging from a certain direction, while interfering signals from other spatial angles of incident are suppressed [2, 9]. Fig. 1 shows a broadband beamformer, where each discretely sampled sensor signal xm [n] is processed by a lter with coecients organized in a vector wm . If the wavefronts of a signal impinging from an angle # arrive delayed by integer multiples of at the M sensors, the lters wm should ....

....w opt = arg min w w H R xx w subject to C H w = f ; 3) where R xx is the covariance matrix built from the input x[n] C the constraint matrix, and f the constraining vector. The choice of C and f will be commented on in Sec. 2.3. An analytic optimum Wiener solution for (3) can be derived [9]. Iterative methods to determine w opt have been suggested, and include the Frost beamformer [2] and the generalised sidelobe canceller (GSC [4] which will be used in the following. 2.2. Generalised Sidelobe Canceller The GSC performs an unconstrained optimization based on a projection of ....

B.D. Van Veen and K.M. Buckley. \Beamforming: A Versatile Approach to Spatial Filtering". IEEE Acoustics, Speech, Signal Processing Magazine, Vol.5(No.2):pp.4-24, April 1988.

....f i #=w#k;f i # H x#k;f i #; 3) where H denotes Hermitian transpose, and w#k; f i # is the N vector of array weights to apply at time k. The objective is to choose the array weights w#k; f i # to give the optimum estimate of the desired signal s#k; f i # (according to some criterion) See [3] for an excellent review of beamforming techniques. Conventional array processing algorithms were developed for traditional applications such as radar, sonar, and communications systems. However, the signal environment in the speech acquisition problem differs significantly from these ....

B.D. Van Veen and K.M. Buckley, "Beamforming: A versatile approach to spatial filtering," IEEE ASSP Mag., vol. 5, no. 2, pp. 4--24, Apr. 1988.

....has the desired beamforming behaviour. 4. COMPARISON WITH STANDARD BEAMFORMING We further compare the performance (SNR of enhanced signal s(k) of the SVD based optimal filtering technique and standard beamforming techniques (delay and sum beamforming and Generalised Sidelobe Canceller (GSC) [9]. This comparison is done for different reverberation times T60 of the room. Low reverberation times correspond to highly correlated noise, while high reverberation times correspond to highly uncorrelated (diffuse) noise. Figure 5 compares the performance of the delay and sum beamformer and the ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, pp. 4--24, Apr. 1988. W99-4

....2: Multi channel filtering 3. COMPARISON WITH STANDARD BEAMFORMING In this section we compare the performance (SNR of the enhanced signal s(k) of the SVD based optimal filtering technique and standard beamforming techniques (delay and sum beamforming and Generalized Sidelobe Canceler (GSC) [8]. The simulated room configuration is depicted in figure 3, with dimensions 7m Theta3:5m Theta 3m. It consists of a microphone array, a speech source and a noise source. The linear equi spaced microphone array has 5 microphones and the distance between two adjacent microphones is 5cm. The speech ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering", IEEE ASSP Magazine, pp. 4--24, Apr. 1988.

....is focused towards the speech source. When considering a localized noise source (and no multipath propagation) it is shown that a zero is steered towards this noise source. Section 4 further compares the performance of the SVD based optimal filtering technique with standard beamforming algorithms [6] (delay and sum, Griffiths Jim and Generalized Sidelobe Canceller (GSC) 7] 8] 9] 10] Adaptive Griffiths Jim beamformers perform particularly well when the noise on the different microphones is highly correlated. When the noise is less correlated, the performance of these beamformers drops ....

....at a different moment than the speechframe, performance will decrease in general. However, by making the noiseframe long enough, performance can be made equally good. 4. 1 Standard beamforming algorithms We will briefly discuss two beamforming techniques : fixed delay and sum beamforming [6][21] and adaptive Griffiths Jim beamforming [7] 8] 9] 10] Figure 23 depicts a fixed delay and sum beamformer. In order to achieve a spatial alignment of the microphone array with the speech source, which impinges on the microphone array at an angle , the different microphone signals m j (k) are ....

B. D. Van Veen and K. M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, pp. 4--24, Apr. 1988.

....[30] Yet another important milestone was the work of Capon who proposed an adaptive antenna system [6] using a look direction constraint that resulted in the minimum variance distortionless beamformer. Further advances were made by Frost [8] and Griffiths and Jim [9] among several others. See [28] for a review on spatial filtering through beamforming. Because of significant delay spread in the channel, array processing in mobile communications can be greatly leveraged by processing the array signals in space and in time (STP) to minimize both co channel interference and inter symbol ....

B. D. Van Veen and K. M. Buckley. "Beamforming: a versatile approach to spatial filtering". IEEE ASSP Magazine, pages 4--24, April 1988.

....BLIND MULTIUSER DETECTION The goal here is to blindly compute linear decorrelation weight vectors to preserve the desired signal and suppress interference, see [5, 10, 11] for prior work. We present our algorithm following the framework of the elegant and well known Generalized Sidelobe Canceler [12]. Let w0 denote the linear detector, and s0 the N dimensional signature sequence vector of the desired user. Constraining the detector to present a unit response to the desired user s signature sequence, and decomposing w0 into corresponding constrained and unconstrained components, we have, w0 = ....

....s0=N . The N Theta (N Gamma 1) matrix Cn spans the null space of s0 . In general, multiple constraints can be imposed on wq , for instance, to exploit the knowledge of signature sequences and timing of other interfering users. Cn is readily obtained via one of many orthogonalization procedures [12]. In fact, for the special case above, Cn can be precomputed off line for each desired signature sequence. wa denotes the N Gamma 1 dimensional adaptive portion of wa . Thus, the output of the ith array element for the lth symbol is given by z i (l) w H o (l)x i (l) w H q x i (l) Gamma ....

[Article contains additional citation context not shown here]

B. D. Van Veen and K. M. Buckley, "Beamforming: A versatile approach to spatial filtering," IEEE ASSP Magazine, Vol. 5, No. 2, pp. 4-24, April 1988.

....the effects of reverberation and additive noise. The microphone array provides a means of mitigating these effects. An array uses a set of spatially distributed sensors to provide signal to noise ratio (SNR) improvement for sound produced in the focal region. Earlier techniques such as beamforming [1] and approximations to inverse filters [2] treat reverberation as noise and seek to remove it from the captured signal. Matched Filter Array (MFA) processing [3] uses reverberant energy to reinforce the desired signal by cohering the reflected source images with the direct wavefront arrival. In ....

Van Veen, B.D. and Buckley, K.M.. "Beamforming: A Versatile Approach to Spatial Filtering." IEEE ASSP Magazine, 5(2), 4--24 (1988).

....ratio (SINR) obtained in the simulations provides an upper bound for the performance of matched filter algorithms that use estimates of the steering vector a( 1 ) for the spatial filter w . 2. The Maximum SINR Bound: The maximum SINR beamformer algorithm is sometimes used in RADAR applications [8], where it is possible to directly estimate the interference covariance matrix. For a given channel realisation, the spatial filter which maximises the output SINR is obtained as: w = Q Gamma1 y a( 1 ) 15) where Q Gamma1 y denotes the matrix inverse operation. This result provides a ....

B.D. Van Veen and K.M. Buckley. "Beamforming: A versatile approach to spatial filtering". IEEE ASSP Mag, pp 4--24, April 1988.

....are sensitive to the position of the source[14] Various signal processing methods have been employed to mitigate the deleterious effects of room acoustics. Beamforming algorithms that electronically aim a microphone array may be applied with varying degrees of sophistication to reduce interference[15, 16]. Often these algorithms are also used to steer a dead spot or null toward one or more unwanted sources. Adaptive beamforming [17, 18, 19] is most useful when the interference is concentrated in a small number of known (measured) directions and or in some known set of frequencies. An overview of ....

....or null toward one or more unwanted sources. Adaptive beamforming [17, 18, 19] is most useful when the interference is concentrated in a small number of known (measured) directions and or in some known set of frequencies. An overview of beamforming algorithms is provided by Van Veen and Buckley [16]. Other noise cancellation techniques may be applied when noise originates from numerous directions, or is isotropic, and, in the adaptive case, when a signal free noise reference measurement can be made [20] Inverse filtering and echo cancellation techniques are applicable when the spectrum of a ....

[Article contains additional citation context not shown here]

B. D. Van Veen and K. M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE ASSP Magazine, 5(2):4--24, April 1988.

....because it allows for interference rejection or coherent combining using various narrow beam antennas or spatial array processing. 1.4.2 Beamforming Conventional beamforming has been used as a means to reduce the effects of both multipath and co channel interference. Van Veen and Buckley [16] have written an excellent tutorial, which expands on the basic ideas presented here, and reviews some of the algorithms which are commonly used. The basic principle of beamforming is that by adding the received signal from several antennas with appropriate amplitude scaling and phase shifting, ....

Barry D. Van Veen and Kevin M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE Acoustics, Speech, and Signal Processing Magazine, pages 4--24, April 1988.

No context found.

Barry D. Van Veen and Kevin M. Buckley, "Beamforming - a versatile approach to spatial filtering," IEEE Acoustics, Speech and Signal Processing Magazine, pp. 4--24, April 1988.

No context found.

Barry D. Van Veen and Kevin M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE Acoustics, Speech, and Signal Processing Magazine, pages 4--24, April 1988.

No context found.

Barry D. Van Veen and Kevin M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, pp. 4-24, April 1988. 242

No context found.

Barry D. Van Veen and Kevin M. Buckley, "Beamforming: A Versatile Approach to Spatial Filtering," IEEE ASSP Magazine, April 1988.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC