Bartlett Beamformer Research Articles

Design of a UWB Antenna with Multiple Ports on a Single Circular Radiator for Direction-Finding Applications

This paper proposes a single circular radiator with a multi-port (SRMP) antenna that can estimate the direction-of-arrival (DoA) in the azimuth and elevation directions. The proposed SRMP antenna is designed to minimize the size of the ultra-wideband system by using only one patch radiator. To verify the feasibility, the proposed antenna is fabricated, and the reflection coefficient and boresight gain are measured (-13.3 dB and 3.4 dBi at 8 GHz). Then, to observe the direction-finding performance, the DoA estimation results using the Bartlett beamformer are compared with the typical array. At all incident angles, a root-mean-square error of less than 1° is observed when the signal-to-noise ratio is higher than 6 dB.

An improved TOA estimation algorithm based on denoised MVDR for B5G positioning

This paper proposes an improved minimum variance distortionless response (MVDR) based TOA estimation algorithm for 5G NR signals under multipath environments. The proposed algorithm achieves high resolution by exploiting a large number of subcarriers of 5G signals and reduces the dimension of the covariance matrix involved in MVDR substantially by utilizing a novel smoothing scheme. Since MVDR requires a relatively high signal-to-noise ratio (SNR), a denoising method is used to improve the TOA estimation performance. Simulation results show that the proposed algorithm achieves much higher resolution than the Bartlett beamformer (BF) and the TOA estimation accuracy remains high over a wide range of SNRs.

Proper Power Azimuth Spectrum Estimation for MIMO Channels via Gans Mapping Inversion

The use of antenna arrays is indispensable in radar and multiple-input multiple-output (MIMO) wireless communications areas, as it permits the treatment of wavefronts in the spatial domain, enabling important applications such as beamforming and target detection. Spatial information is commonly given in terms of spatial correlation functions (SCFs), but its representation in terms of angular domain, such as the power azimuth spectrums (PASs), is sometimes more convenient. Therefore, transforming from SCF to PAS, and vice versa, is often required. This is commonly done by employing so-called beamformers, where the Bartlett beamformer (BB) is the most commonly utilized. However, the use of beamformers alone is not enough for retrieving PAS information from a given SCF. Particularly, this paper shows that a non-linear operation is missing in relating SCFs to PASs as provided by current beamformers. The paper also shows the mathematical expressions that correctly relate SCFs to PASs and wavenumber spectrums (WNSs) for the general case of systems with antenna arrays. The developed theory results in two new beamformers, which, corroborated by simulation results, solve any previous inconsistency in estimating PASs from SCFs.

A Power-Angle-Spectrum Based Clustering and Tracking Algorithm for Time-Varying Radio Channels

Radio channel modeling has been an important research topic, since the performance of any communication system depends on channel characteristics. So far, most existing clustering algorithms are conducted based on the multipath components (MPCs) extracted by using a high-resolution parameter estimation approach, e.g., SAGE or MUSIC, etc. However, most of the estimation approaches require prior information to extract MPCs. Moreover, the high-resolution estimation approaches usually result in relatively high complexity, and thus, the clusters can only be identified by using an offline approach after the measurements. Therefore, a power-angle-spectrum (PAS) based clustering and tracking algorithm (PASCT) is proposed in this paper. First, a PAS is extracted from measurement data by using a Bartlett beamformer. For each PAS, the potential targets are selected from the background and separated into clusters by using image processing approaches. The recognized clusters are characterized by the following three attributes: size, position, and shape feature, where an orientation histogram is developed to describe the shape feature of the clusters. Moreover, a cost minimizing tracking approach based on Kuhn–Munkres method is proposed to accurately identify the clusters in non-stationary channels. The proposed PASCT algorithm is validated based on both simulations and measurements. It is found that the dominating clusters in both line-of-sight and non-line-of-sight environments can be well recognized and tracked with the proposed algorithm. By using the proposed algorithm, the dynamic changes of the clusters in real-time channel measurements, e.g., number, birth–death process, and size of the clusters, can be well observed. Through the experiments, the proposed algorithm can achieve fairly good accuracy on the cluster identification with lower complexity compared to the conventional solution.

Passive acoustic localization of North Atlantic Right Whales using a modified near-field Bartlett beamformer

Owing to the principle of least commitment, near-field beamformers can produce passive acoustic source localizations which are robust to noise and interference. The power output of a traditional Bartlett near-field beamformer may be formulated in terms of the pairwise cross correlation functions of the sensor signals. We present a modified Bartlett processor wherein the ordinary cross correlation is replaced by generalized cross correlation, generalized in both time and frequency. As an example of the utility of the technique, we present results from a six element pentagonal marine array with a baseline of approximately 15 km deployed off the coast of Virginia. Localization of synthetic FM sweeps from known source locations within the array yield deviations from the true source location as measured by GPS of less than 100 meters. Localization of actual North Atlantic Right Whale calls provide good alignment of the unknown channel arrivals and acceptably small error ellipses.

A Dynamic Wideband Directional Channel Model for Vehicle-to-Vehicle Communications

Vehicle-to-vehicle (V2V) communications have received a lot of attention due to their numerous applications in traffic safety. The design, testing, and improvement of the V2V system hinge critically on the understanding of the propagation channels. An important feature of the V2V channel is the time variance. To statistically model the time-variant V2V channels, a dynamic wideband directional channel model is proposed in this paper, based on measurements conducted at 5.3 GHz in suburban, urban, and underground parking environments. The model incorporates both angular and delay domain properties and the dynamic evolution of multipath components (MPCs). The correlation matrix distance is used to determine the size of local wide-sense stationary (WSS) region. Within each WSS time window, MPCs are extracted using the Bartlett beamformer. A multipath distance-based tracking algorithm is used to identify the “birth” and “death” of such paths over different stationarity regions, and the lifetime of MPC is modeled with a truncated Gaussian distribution. Distributions for the number of multipaths and their positions are statistically modeled. Within each path lifetime, the initial power is found to depend on the excess delay, and a linear polynomial function is used to model the variations within the lifetime. In addition, a Nakagami distribution is suggested to describe the fading behavior. Finally, the model implementation is validated by comparison of second-order statistics between measurements and simulations.

Design Smart Antenna by Microstrip Patch Antenna Array

Smart have been studied extensively this decade because of its low profile structure and formidable rate, thereby creating new and improved services at lower costs. They are extremely compatible for embedded in handheld wireless devices such as cellular phones, pagers etc. Because of its versatility, Smart antenna which is designed by planer array can be used to synthesize a required pattern that cannot be achieved with a single patch element. Index Terms—Radiation patterns, Mobile communication, planar array, PCCAD 5.0 software etc. I. I NTRODUCTION In high-performance aircraft, spacecraft, satellite and missile application, where size, weight, cost, performance, ease of installation, and aerodynamic profile are constraints, so low profile may be required. Presently there are many other government and commercial applications, such as mobile, radio and wireless communications that have similar specifications .To meet these requirements antennas have been researched extensively. This has resulted in an increase in airtime usage and in the number of subscribers. Spatial processing is the central idea of smart- antenna systems. Although it might seem that smart have been recently discovered, they date back to World War II with the conventional Bartlett beamformer (1). It is only of today's advancement in powerful low-cost digital signal processors, general purpose processors (and ASICs—Application-Specific Integrated Circuits), as well as innovative software-based signal-processing techniques (algorithms), that smart antenna systems have received enormous interest worldwide. To approach the feature, design smart antenna by microstrip patch antenna array (2). Quality factor (Q) of microstrip is a very high. Quality factor can be reduced by increasing the dielectric substrate. But due to increasing thickness, unwanted power loss occurs by the surface wave. However, this surface waves can be minimized by the use of photonic bandgap structures (3). Recent studies on microstrip have primarily concentrated on the improvement of bandwidth and on the design of multifunction operations (4)-(7). As a result, almost 100% bandwidth in terms of VSWR and dual-band

Robust matched-field processor in the presence of geoacoustic inversion uncertainty

This presentation examines the performance of a matched-field processor incorporating geoacoustic inversion uncertainty. Uncertainty of geoacoustic parameters is described via a joint posterior probability distribution (PPD) of the estimated environmental parameters, which is found by formulating and solving the geoacoustic inversion problem in a Bayesian framework. The geoacoustic inversion uncertainty is mapped into uncertainty in the acoustic pressure field. The resulting acoustic field uncertainty is incorporated in the matched-field processor using the minimum variance beamformer with environmental perturbation constraints (MV-EPC). The constraints are estimated using the ensemble of acoustic pressure fields derived from the PPD of the estimated environmental parameters. Using a data set from the ASIAEX 2001 East China Sea experiment, tracking performance of the MV-EPC beamformer is compared with the Bartlett beamformer using the best-fit model.

Robust nonadaptive matched‐field beamforming in an uncertain ocean environment.

Matched‐field processing techniques can be both ambiguity‐prone and sensitive to errors in the assumed environmental conditions. Although greater robustness to environmental variability can be obtained by the use of data adaptive methods, such as the MV‐EPC beamformer [J. L. Krolik, J. Acoust. Soc. Am. 92, 1408–1419 (1992)] or joint estimation of source and channel parameters [D. F. Gingras and P. Gersoft, J. Acoust. Soc. Am. 97, 3589–3598 (1995)], these strategies require higher signal‐to‐noise ratios. The methods presented here concern the design of robust nonadaptive beamformer weights with sidelobe levels which are less signal‐to‐noise ratio dependent. As with Chebyshev filters, the weights are designed to minimize the maximum magnitude‐squared sidelobe level. Robustness to environmental mismatch is achieved by defining the sidelobe level as the magnitude‐squared response averaged over an ensemble of environmental conditions. The two algorithms proposed are a fast iterative constrained minimum variance method and the use of a minimax quadratic programming technique. For an uncertain Mediterranean environment, an improvement in the maximum average sidelobe level of as much as 3 dB over the Bartlett beamformer is achieved. [Work supported by NRaD/ONR.]

The performance of matched-field beamformers with Mediterranean vertical array data

Minimum variance (MV) adaptive beamforming has been widely proposed for matched-field processing because it provides a means of suppressing ambiguous beampattern sidelobes. A difficulty with MV methods, however, is their sensitivity to signal wavefront mismatch. In this work, the performance of three robust MV methods and the Bartlett beamformer is evaluated using vertical array data from the Mediterranean Sea collected by the NATO SACLANT Centre. The three MV methods considered are: (1) the reduced MV beamformer (RMV), (2) the MV beamformer with neighborhood location constraints (MV-NLC), (3) the MV beamformer with environmental perturbation constraints (MV-EPC). While the Bartlett, RMV, and MV-NLC methods assume the ocean environment is known precisely, the MV-EPC method models the environment as being random with known statistics. Experimental and companion simulation results indicate that for modest environmental uncertainty, the MV-EPC beamformer achieves a higher probability of correct localization and better sidelobe performance than the other three methods.

COMPARISON OF LINEAR AND ORTHOGONAL BEAMFORMER PERFORMANCE FOR THE 1993 MATCHED FIELD PROCESSING BENCHMARKS

Results are presented for the Matched Field Processing (MFP) analysis of synthetic benchmark cases, performed by a comprehensive Acoustic Signal Processing (ASP) code used in a turnkey manner. The performance of the Generalized Bartlett Beamformer (GBB), Minimum Variance (MV), and Modified Reduced Minimum Variance (MRMV) processors incorporated in the ASP code were evaluated. Matches for replicas generated using normal mode and Parabolic Equation (PE) models produced virtually identical results. However, the choice of layered versus gradient models was shown to be a cause of sufficient mismatch and to alter the source position by several increments in range and depth if sufficiently fine layering was not employed. GBB and MRMV exhibit similar levels of robustness to mismatch, while MV showed its well-known sensitivity to mismatch. Our turnkey approach indicated that MFP techniques are relatively robust with respect to source detection and localization even when suboptimal modeling and processing parameters are used.

A nearest neighbor algorithm for fast matched-field processing with a vertical line array

Selection of replica fields that are most like the data, i.e., the nearest neighbors (NNs) to the data, offers a way of reducing the computational search space in matched-field processing, thereby making larger physical search spaces or a larger number of frequencies practical. To enable selection of NNs a vector basis for the search space is required. The authors use the large eigenvectors of the covariance matrix for uncorrelated sources spread over the search region. This is not only a suitable vector basis of the search space, but also results in a dimensional reduction from the full set of eigenvectors, with a further computational saving. The replica vectors for the search region are partitioned by finding their projection on this vector basis. One can then select for matching only those replicas with similar squared projections on the vector basis. This selection process carries a modest cost in computing overhead, provided that the code, the partitioning, and the replica selection parameters are optimized. The detection performance and false alarm probability for the Bartlett beamformer, with and without selection of the replicas, were estimated from simulations of noisy data received on a vertical line array at practical time-bandwidth products. An order of magnitude speedup was obtained.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Optimal array configurations for a Bartlett beamformer in an Arctic environment

Optimal or near-optimal array configurations for a vertical array in a shallow-water Arctic environment were determined using a Bartlett matched-field beamformer. A normal mode model was employed to calculate the acoustic field for a range-independent waveguide, and a simulated annealing (SA) algorithm was implimented to solve the combinitorial aspect of this problem. The cost function was designed to minimize sidelobes and the mainlobe width in the ambiguity surface, with the objective of optimizing the localization accuracy of the Bartlett beamformer. Exhaustive searches, which are possible for arrays with up to five hydrophones, confirmed the accuracy of array configurations from the SA method. An analysis of the range dependence of these solutions compares the localization accuracy from optimal and conventional uniform arrays for 8, 16, and 32 hydrophones at source ranges between 10 and 40 km.

Replica partitioning and preselection for faster matched-field processing.

Matched-field processing requires the evaluation of the inner product of the measured and replica fields at a grid of points covering the search region. This process may require a significant computational time despite the increased speed of computers. A way of reducing the search space is described and evaluated. First, a basis for the signal space is found for all possible source positions. Then the replica fields for the search region are partitioned into groups with similar excitations of the basis vectors used to represent the replicas. One can then quickly select the group of replicas that is most like any data to be matched, and then do a detailed search over only that group to find the best match. An example is shown of the detection and localization performance of the Bartlett beamformer with and without preselection of the replicas. A reduction in computation time of 10 to 20 was achieved with only a slight loss in performance over a wide range of signal-to-noise ratios.

Three‐dimensional matched‐field processing with an eigenvalue method

An eigenvalue method for three‐dimensional matched‐field processing with a vertical array has been developed for localization of multiple sources in range and depth (bearing can also be determined with the method if the environment is asymmetric). The method involves applying the Bartlett beamformer to the eigenvectors of the cross‐spectral density matrix. This approach appears to be more effective than the standard eigenvalue approach involving beamforming on a linear combination of several eigenvectors. Eigenvalue beamforming methods are based on the orthogonal targets approximation [R. F. Gragg, NRL Rep. 9143, Naval Research Laboratory, Washington, DC (1989)]. The spatial correlation over a horizontal array of two sources is small provided the sources are sufficiently separated in bearing. On the other hand, the spatial correlation over a vertical array of two point sources may be relatively large for some source locations (i.e., the Bartlett matched‐field processor for a vertical array has relatively large sidelobes). However, simulations suggest that this effect does not seriously degrade the eigenvalue processing method for vertical arrays. Source motion will further enhance this processing method.