Zhiqun Daniel Deng

Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements

Locating the position of fixed or mobile sources (i.e., transmitters) based on measurements obtained from sensors (i.e., receivers) is an important research area that is attracting much interest. In this paper, we review several representative localization algorithms that use time of arrivals (TOAs) and time difference of arrivals (TDOAs) to achieve high signal source position estimation accuracy when a transmitter is in the line-of-sight of a receiver. Circular (TOA) and hyperbolic (TDOA) position estimation approaches both use nonlinear equations that relate the known locations of receivers and unknown locations of transmitters. Estimation of the location of transmitters using the standard nonlinear equations may not be very accurate because of receiver location errors, receiver measurement errors, and computational efficiency challenges that result in high computational burdens. Least squares and maximum likelihood based algorithms have become the most popular computational approaches to transmitter location estimation. In this paper, we summarize the computational characteristics and position estimation accuracies of various positioning algorithms. By improving methods for estimating the time-of-arrival of transmissions at receivers and transmitter location estimation algorithms, transmitter location estimation may be applied across a range of applications and technologies such as radar, sonar, the Global Positioning System, wireless sensor networks, underwater animal tracking, mobile communications, and multimedia.

Improving hydroturbine pressures to enhance salmon passage survival and recovery

Barotrauma caused by rapid decompression during hydroturbine (turbine) passage may occur as fish move through the low pressure region below the turbine runner. This scenario is of particular concern in North American rivers with populations of ESA-listed salmon. The US Army Corps of Engineers (USACE) and the Pacific Northwest National Laboratory released Sensor Fish into lower Snake and Columbia River turbines to determine the magnitude and rate of pressure change fish might experience. Recorded pressures were applied to simulated turbine passage (STP) in laboratory studies to determine the effect of rapid decompression on juvenile Chinook salmon. These STP studies have increased our understanding of how pressure effects fish passing through turbines and suggest that the ratio of pressure change [acclimation pressure (the depth upstream of the dam where fish are neutrally buoyant) divided by nadir pressure (lowest pressure)] is highly predictive in determining the effect on smolt survival. However, uncertainty remains in smolt acclimation depth prior to entering turbine intakes at hydroelectric facilities. The USACE continues to make progress on salmon survival and recovery efforts through continued research and by applying pressure study results to turbine design. Designing new turbines with higher nadir pressure criteria is likely to provide safer fish passage for all salmonid species experiencing turbine passage.

Design parameters of a miniaturized piezoelectric underwater acoustic transmitter.

PZT ceramics have been widely used in underwater acoustic transducers. However, literature available discussing the design parameters of a miniaturized PZT-based low-duty-cycle transmitter is very limited. This paper discusses some of the design parameters—the backing material, driving voltage, PZT material type, power consumption and the transducer length of a miniaturized acoustic fish tag using a PZT tube. Four different types of PZT were evaluated with respect to the source level, energy consumption and bandwidth of the transducer. The effect of the tube length on the source level is discussed. The results demonstrate that ultralow-density closed-cell foam is the best backing material for the PZT tube. The Navy Type VI PZTs provide the best source level with relatively low energy consumption and that a low transducer capacitance is preferred for high efficiency. A 35% reduction in the transducer length results in 2 dB decrease in source level.

Feasibility of Tracking Fish with Acoustic Transmitters in the Ice Harbor Dam Tailrace

The Juvenile Salmon Acoustic Telemetry System (JSATS) has been used at many dams but has never been deployed in the near-dam tailrace environment. The use of JSATS in the tailrace is of interest to fishery managers to evaluate downstream passage behavior of juvenile salmonids and dam approach behavior of upstream migrating adult salmon and lamprey. The acoustic noise level and detection range of JSATS were studied to determine the feasibility of deploying JSATS in the Ice Harbor Dam tailrace. The noise level measured from the powerhouse deck was less than 104 dB re 1 μPa except for the turbine outlet near the spillway, and 350 m downstream of the dam, the noise level was less than 106 dB. The measured noise levels would allow a theoretical detection range of 100 m to 350 m and 85 m to 320 m, respectively. Validation experiments showed that the detection range is 113 to 184 m using hydrophones deployed from the powerhouse deck and 148 m using hydrophones deployed 500 m downstream of the dam.

Aquatic Acoustic Metrics Interface Utility for Underwater Sound Monitoring and Analysis

Fishes and marine mammals may suffer a range of potential effects from exposure to intense underwater sound generated by anthropogenic activities such as pile driving, shipping, sonars, and underwater blasting. Several underwater sound recording (USR) devices have been built to acquire samples of the underwater sound generated by anthropogenic activities. Software becomes indispensable for processing and analyzing the audio files recorded by these USRs. In this paper, we provide a detailed description of a new software package, the Aquatic Acoustic Metrics Interface (AAMI), specifically designed for analysis of underwater sound recordings to provide data in metrics that facilitate evaluation of the potential impacts of the sound on aquatic animals. In addition to the basic functions, such as loading and editing audio files recorded by USRs and batch processing of sound files, the software utilizes recording system calibration data to compute important parameters in physical units. The software also facilitates comparison of the noise sound sample metrics with biological measures such as audiograms of the sensitivity of aquatic animals to the sound, integrating various components into a single analytical frame. The features of the AAMI software are discussed, and several case studies are presented to illustrate its functionality.

A small long-life acoustic transmitter for studying the behavior of aquatic animals

Acoustic telemetry is an important tool for studying the behavior of aquatic animals and assessing the environmental impact of structures such as hydropower facilities. However, the physical size, signal intensity, and service life of off-the-shelf transmitters are presently insufficient for monitoring certain species. In this study, we developed a small, long-life acoustic transmitter with an approximate length of 24.2 mm, diameter of 5.0 mm, and dry weight of 0.72 g. The transmitter generates a coded acoustic signal at 416.7 kHz with a selectable source level between 159 and 163 dB relative to 1 μPa at 1 m, allowing a theoretical detection range of up to 500 m. The expected operational lifetime is 1 yr at a pulse rate interval of 15 s. The new technology makes long-term acoustic telemetry studies of small fish possible, and is being deployed for a long-term tracking of juvenile sturgeon.

A Cloud-Based Decision Support System Framework for Hydropower Biological Evaluation

Hydropower is one of the most important energy sources: it accounts for more than 80% of the world’s renewable electricity and 16% of the world’s electricity. Significantly more hydropower capacity is planned to be developed. However, hydro-structures, including hydroelectric dams, may have adverse biological effects on fish, especially on migratory species. For instance, fish can be injured or even killed when they pass through turbines. This is why biological evaluations on hydro-structures are needed to estimate fish injury and mortality rates. The Hydropower Biological Evaluation Toolset (HBET) is an integrated suite of science-based desktop tools designed to evaluate whether the hydraulic conditions of hydropower structures are fish friendly by analyzing collected data and providing estimated injury and mortality rates. The Sensor Fish, a small autonomous sensor package, is used by HBET to record data describing the conditions that live fish passing through a hydropower structure will experience. In this paper, we present a plan to incorporate cloud computing into HBET, and migrate into a cloud-based decision support system framework for hydropower biological evaluation. These enhancements will make the evaluation system more scalable and flexible; however, they will also introduce a significant challenge: how to maintain security while retaining scalability and flexibility. We discuss the technical methodologies and algorithms for the proposed framework, and analyze the relevant security issues and associated security countermeasures.

Improving underwater localization accuracy with machine learning

Machine learning classification and regression algorithms were applied to calibrate the localization errors of a time-difference-of-arrival (TDOA)-based acoustic sensor array used for tracking salmon passage through a hydroelectric dam on the Snake River, Washington, USA. The locations of stationary and mobile acoustic tags were first tracked using the approximate maximum likelihood algorithm. Next, ensembles of classification trees successfully identified and filtered data points with large localization errors. This prefiltering step allowed the creation of a machine-learned regression model function, which decreased the median distance error by 50% for the stationary tracks and by 34% for the mobile tracks. It also extended the previous range of sub-meter localization accuracy from 100 m to 250 m horizontal distance from the dam face (the receivers). Median distance errors in the depth direction were especially decreased, falling from 0.49 m to 0.04 m in the stationary tracks and from 0.38 m to 0.07 m in the mobile tracks. These methods would have application to the calibration of error in any TDOA-based sensor network with a steady environment and array configuration.