Array signal processing for maximum likelihood direction-of-arrival estimation

Emitter Direction-of-Arrival (DOA) estimation is a fundamental problem in a variety of applications including radar, sonar, and wireless communications. The research has received considerable attention in literature and numerous methods have been proposed. Maximum Likelihood (ML) is a nearly optimal technique producing superior estimates compared to other methods especially in unfavourable conditions, and thus is of significant practical interest. This paper discusses in details the techniques for ML DOA estimation in either white Gaussian noise or unknown noise environment. Their performances are analysed and compared, and evaluated against the theoretical lower bounds

Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

Listening for Sirens: Locating and Classifying Acoustic Alarms in City Scenes

This paper is about alerting acoustic event detection and sound source localisation in an urban scenario. Specifically, we are interested in spotting the presence of horns, and sirens of emergency vehicles. In order to obtain a reliable system able to operate robustly despite the presence of traffic noise, which can be copious, unstructured and unpredictable, we propose to treat the spectrograms of incoming stereo signals as images, and apply semantic segmentation, based on a Unet architecture, to extract the target sound from the background noise. In a multi-task learning scheme, together with signal denoising, we perform acoustic event classification to identify the nature of the alerting sound. Lastly, we use the denoised signals to localise the acoustic source on the horizon plane, by regressing the direction of arrival of the sound through a CNN architecture. Our experimental evaluation shows an average classification rate of 94%, and a median absolute error on the localisation of 7.5{\deg} when operating on audio frames of 0.5s, and of 2.5{\deg} when operating on frames of 2.5s. The system offers excellent performance in particularly challenging scenarios, where the noise level is remarkably high.Comment: 6 pages, 9 figure

WiFi emission-based vs passive radar localization of human targets

In this paper two approaches are considered for human targets localization based on the WiFi signals: the device emission-based localization and the passive radar. Localization performance and characteristics of the two localization techniques are analyzed and compared, aiming at their joint exploitation inside sensor fusion systems. The former combines the Angle of Arrival (AoA) and the Time Difference of Arrival (TDoA) measures of the device transmissions to achieve the target position, while the latter exploits the AoA and the bistatic range measures of the target echoes. The results obtained on experimental data show that the WiFi emission-based strategy is always effective for the positioning of human targets holding a WiFi device, but it has a poor localization accuracy and the number of measured positions largely depends on the device activity. In contrast, the passive radar is only effective for moving targets and has limited spatial resolution but it provides better accuracy performance, thanks to the possibility to integrate a higher number of received signals. These results also demonstrate a significant complementarity of these techniques, through a suitable experimental test, which opens the way to the development of appropriate sensor fusion techniques

Spatial channel characterization for smart antenna solutions in FDD wireless networks

This paper introduces a novel metric for determining the spatial decorrelation between the up- and down-link wireless bearers in frequency division duplex (FDD) networks. This metric has direct relevance to smart or adaptive antenna array base-station deployments in cellular networks, which are known to offer capacity enhancement when compared to fixed coverage solutions. In particular, the results presented were obtained from field trial measurement campaigns for both urban and rural scenarios, with the observations having a direct impact on the choice of down-link beamforming architecture in FDD applications. Further, it is shown that significant spatial decorrelation can occur in urban deployments for bearer separations as small as 5 MHz. Results are presented in terms of both instantaneous characteristics as well as time averaged estimates, thus facilitating the appraisal of smart antenna solutions in both packet and circuit switched network

The JDTDOA algorithm applied to signal recovery : a performance analysis

This article suggests a novel method to retrieve a narrowband signal sent in a multipath environment with a delay spread considering ISI between symbols. The proposed method does not require any preamble nor known signal. Using the joint direction and time delay of arrivals estimation algorithm developed in prior work, the directions and time delays of arrival in the multipath channel are jointly estimated and associated while keeping a low computational cost. In this process, a MVDR beamformed copy of each arriving signal is created. The quality of these “pseudo copies” is evaluated and compared to the original direct and reflected signals in this work. Another beamforming method, the Moore–Penrose pseudoinverse, with better retrieval of the direct and reflected signals is also proposed. Using a simple delay-and-sum operation on the previously beamformed copies, it is possible to substantially improve the the system’s performance in terms of bit error rate. An approach using oversampling on the array antenna is introduced to improve performance. Numerical simulations are discussed to support theory