Vandermonde invariance transformation

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

et al. 2014

Sensor arrays with Vandermonde or centro-hermitian responses cannot always be constructed. However, such array response structure can be achieved by means of a mapping which transforms the real array response to an array response with the desired properties by applying array interpolation algorithms.In this work a low-complexity, multi-sector, signal adaptive array interpolation approach that achieves low transformation bias in the presence of highly correlated signals is presented. Estimation of Signal Parameters via Rotational Invariance (ESPRIT) algorithm with Forward Backward Average (FBA) and Spatial Smoothing (SPS) as well as model order estimation is applied after array interpolation in conjunction with the Vandermonde Invariance Transformation (VIT) to obtain precise high resolution estimates in closed form. A set of numerical simulations show that the proposed approach provides precise estimates for arbitrary array responses in highly correlated signal signal environments.

“…Finally, from the first set of estimates the VIT [17] can be applied followed byd extra applications of ESPRIT to obtain more precise estimates.…”

Section: Gevd and Espritmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A signal adaptive array interpolation approach with reduced transformation bias for DOA estimation of highly correlated signals

Marinho

Antreich

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

et al. 2014

“…In order to further improve the accuracy of DoA estimation schemes, preprocessing schemes can be applied beforehand. We consider in this work the Vandermonde Invariation Technique (VIT) [58], Spatial smoothing (SPS) [59], and Forward Backward Averaging (FBA) [60,61] as a preprocessing schemes. As depicted in Figure 3, after the 6 Wireless Communications and Mobile Computing Delay And Sum [38] DS ( ) =…”

Section: Doa Estimation Framework According Tomentioning

confidence: 99%

Low Cost Antenna Array Based Drone Tracking Device for Outdoor Environments

Oliveira

Miranda

Wireless Communications and Mobile Computing

et al. 2019

Applications of direction of arrival (DoA) techniques have dramatically increased in various areas ranging from the traditional wireless communication systems and rescue operations to GNSS systems and drone tracking. Particularly, police forces and security companies have drawn their attention to drone tracking devices, in order to provide the safeness of citizens and of clients, respectively. In this paper, we propose a low cost antenna array based drone tracking device for outdoor environments. The proposed solution is divided into hardware and software parts. The hardware part of the proposed device is based on off-the-shelf components such as an omnidirectional antenna array, a 4-channel software defined radio (SDR) platform with carrier frequency ranging from 70 MHz to 6 GHz, a FPGA motherboard, and a laptop. The software part includes algorithms for calibration, model order selection (MOS), and DoA estimation, including specific preprocessing steps and a tensor-based estimator to increase the DoA accuracy. We evaluate the performance of our proposed low cost solution in outdoor scenarios. According to our measurement campaigns, we show that when the array is in the front fire position, i.e., with a DoA ranging from -60° to 60°, the maximum and the average DoA errors are 6° and 1,9°, respectively.

High accuracy and low complexity adaptive Generalized Sidelobe Cancelers for colored noise scenarios

Miranda

Digital Signal Processing

Antreich

2014

The Generalized Sidelobe Canceler (GSC) is a beamforming scheme which is applied in many fields such as audio, RADAR, SONAR and telecommunications. Recently, the adaptive Reduced Rank GSC (RR-GSC) has been proposed for applications with a large number of sensors. Due to its dimensionality reduction step, the adaptive RR-GSC achieves an enhanced performance in comparison with the standard GSC. However, both standard GSC and RR-GSC have their performance drastically degraded in the presence of colored noise. In this paper, we propose to extend further the GSC and the RR-GSC for colored noise scenarios. As shown in this paper, such improvement in colored noise scenarios can be obtained by incorporating a stochastic or a deterministic prewhitening step in the GSC and RR-GSC algorithms. Since the prewhitening increases the computational complexity, a block-wise reduced rank stochastic gradient GSC beamformer is also proposed. The block-wise step allows only one prewhitening step per block while in the previous schemes one per sample was needed. Another proposed advance in colored noise scenarios is the incorporation of the Vandermonde Invariance Transform (VIT). The VIT works as a pre-beamformer which reduces the interferent power of the undesired sources and the colored noise effect. We show by means of simulations the improved results even for highly correlated scenarios.