Robert D. Tingley

Indoor geolocation in the absence of direct path

Severe multipath in indoor areas causes undetected direct path (UDP) conditions, which pose a serious challenge to the design of robust precision indoor geolocation systems. Based on a scenario on the third floor of the Atwater Kent Laboratory at the Worcester Polytechnic Institute, we explain the reason for frequent absence of direct path, and introduce and analyze the effectiveness of two novel approaches to mitigating the large ranging errors caused by UDP conditions. The first technique exploits nondirect paths for ranging, while the second approach relies on cooperative localization for wireless sensor and ad hoc networks

Space-time measurement of indoor radio propagation

Most existing techniques for indoor radio propagation measurement do not resolve the angles from which signal components arrive at the receiving antenna. Knowledge of the angle-of-arrival is required for evaluation of evolving systems that employ smart antenna technology to provide features such as geolocation, interference cancellation, and space-division multiplexing. This paper presents a novel technique for the joint measurement of the angles, times and complex amplitudes of discrete path arrivals in an indoor propagation environment. A data acquisition system, based upon a vector network analyzer and multichannel antenna array is described, together with its use to collect channel measurement matrices. The inherent error sources present in these measurement matrices are investigated using a compact indoor anechoic range. Two signal processing algorithms are presented whereby the channel parameters may be estimated from raw measurements. In the first approach, an optimum beamformer is derived which compensates for systematic errors in the data acquisition system. This approach features very low computational complexity, and delivers modest resolution of path components. The second algorithm is based upon the maximum likelihood criterion, using the measured calibration matrices as space-time basis functions. This algorithm provides super-resolution of all path parameters, at the cost of increased computation. Several example measurements are given, and future directions of our research are indicated.

Autoregressive modeling of analytical sensor data can yield classifiers in the predictor coefficient parameter space

SUMMARY The analysis of chromatographic data resulting from complex chemical mixtures is challenging. Components may co-elute, causing their signals to overlap. An algorithm that will increase the signal-to-noise ratio so compounds present in low abundance can be better distinguished from noise is useful in this type of analysis. The autoregressive (AR) filter offers the advantage of smoothing chromatograms to increase this ratio, while also offering data compression and increased resolution. Furthermore, this filter can be useful for classification, as the roots of the predictor coefficient vectors represent features present in the data and can therefore be used for pattern recognition. In this paper, we present a novel method for applying AR filtering to chromatogram data. We show that the AR filter outperforms the Savitzky-Golay filter for smoothing noise while retaining important information within chromatograms, and also that AR correlation coefficients have the potential to be used to classify chromatogram data into groups. CONTACT cdavis@draper.com.

Upslope propagation of low frequency deep ocean signals

Over the period 18–21 March, 2017, 1-hour waveforms in the 60–120 Hz band were transmitted from a HLF-6A source deployed at 300 m depth in the deep northeast Pacific Ocean. These transmissions were recorded by two vertical hydrophone line arrays at various ranges in the deep ocean, GPS-equipped sonobuoys deployed on the continental shelf, and a bottom-mounted hydrophone in 900-m water at the western edge of Monterey Bay operated by the Monterey Bay Aquarium and Research Institute (MBARI). Although the source-receiver ranges to the sonobuoys and the MBARI hydrophone were approximately the same, the bathymetry profile up the continental slope to the sonobuoy location was significantly steeper than to the MBARI hydrophone. Only the upper part of the frequency band, above 90–95 Hz, is received with good signal-to-noise ratio, illustrating the high-pass temporal filtering of upslope propagation. Upslope propagation also acts as a low-pass spatial filter, allowing only lower-order modes to propagate onto the shelf. Numerical modeling is used to examine the predictability of the measured travel times and multipath arrival structure.Over the period 18–21 March, 2017, 1-hour waveforms in the 60–120 Hz band were transmitted from a HLF-6A source deployed at 300 m depth in the deep northeast Pacific Ocean. These transmissions were recorded by two vertical hydrophone line arrays at various ranges in the deep ocean, GPS-equipped sonobuoys deployed on the continental shelf, and a bottom-mounted hydrophone in 900-m water at the western edge of Monterey Bay operated by the Monterey Bay Aquarium and Research Institute (MBARI). Although the source-receiver ranges to the sonobuoys and the MBARI hydrophone were approximately the same, the bathymetry profile up the continental slope to the sonobuoy location was significantly steeper than to the MBARI hydrophone. Only the upper part of the frequency band, above 90–95 Hz, is received with good signal-to-noise ratio, illustrating the high-pass temporal filtering of upslope propagation. Upslope propagation also acts as a low-pass spatial filter, allowing only lower-order modes to propagate onto the sh...