Abstract:A dual-rate Kalman Filter (DRKF) has been developed to integrate the time-differenced GPS carrier phases and the GPS pseudoranges with INS measurements. The time-differenced GPS carrier phases, which have low noise and millimeter measurement precision, are integrated with INS measurements using a Kalman Filter with high update rates to improve the performance of the integrated system. Since the time-differenced GPS carrier phases are only relative measurements, when integrated with INS, the position error of t… Show more
“…GPS errors are well documented, and there are established methods of filtering data for reducing them as much as possible depending on the particular receiver used (e.g., Hide, et al 2003;Han and Wang 2012). Camera pitch and roll mostly affect altitude errors, which are not a significant concern in most marine mammal research where the targets are on the ocean's surface; however, they could be more important if the system was used with terrestrial or airborne animals.…”
To maintain the benefits of group membership, social animals need mechanisms to stay together and reunite if separated. This thesis explores the acoustic signals that dolphins use to overcome this challenge and mediate their complex relationships in a dynamic 3D environment. Bottlenose dolphins are the most extensively studied toothed whale, but research on acoustic behavior has been limited by an inability to identify the vocalizing individual or measure inter-animal distances in the wild. This thesis resolves these problems by simultaneously deploying acoustic tags on closely-associated pairs of known animals. These first reported deployments of acoustic tags on dolphins allowed me to characterize temporal patterns of vocal behavior on an individual level, uncovering large variation in vocal rates and inter-call waiting time between animals. Looking more specifically at signature whistles, a type of call often linked to cohesion, I found that when one animal produced its own signature whistle, its partner was more likely to respond with its own whistle. To better evaluate potential cohesion functions for signature whistles, I then modeled the probability of an animal producing a signature whistle at different times during a temporary separation and reunion from its partner. These data suggest that dolphins use signature whistles to signal a motivation to reunite and to confirm identity prior to rejoining their partner. To examine how cohesion is maintained during separations that do not include whistles, I then investigated whether dolphins could keep track of their partners by passively listening to conspecific echolocation clicks. Using a multi-pronged approach, I demonstrated that the passive detection range of echolocation clicks overlaps with the typical separation ranges of Sarasota mother-calf pairs and that the amount of time since an animal was last able to detect a click from its partner helped explain its probability of producing a signature whistle. Finally, this thesis developed a portable stereo camera system to study cohesion in situations where tagging is not possible. Integrating a GPS receiver, an attitude sensor and 3D stereo photogrammetry, the system rapidly positions multiple animals, grounding behavioral observations in quantitative metrics and characterizing fine-scale changes that might otherwise be missed.
“…GPS errors are well documented, and there are established methods of filtering data for reducing them as much as possible depending on the particular receiver used (e.g., Hide, et al 2003;Han and Wang 2012). Camera pitch and roll mostly affect altitude errors, which are not a significant concern in most marine mammal research where the targets are on the ocean's surface; however, they could be more important if the system was used with terrestrial or airborne animals.…”
To maintain the benefits of group membership, social animals need mechanisms to stay together and reunite if separated. This thesis explores the acoustic signals that dolphins use to overcome this challenge and mediate their complex relationships in a dynamic 3D environment. Bottlenose dolphins are the most extensively studied toothed whale, but research on acoustic behavior has been limited by an inability to identify the vocalizing individual or measure inter-animal distances in the wild. This thesis resolves these problems by simultaneously deploying acoustic tags on closely-associated pairs of known animals. These first reported deployments of acoustic tags on dolphins allowed me to characterize temporal patterns of vocal behavior on an individual level, uncovering large variation in vocal rates and inter-call waiting time between animals. Looking more specifically at signature whistles, a type of call often linked to cohesion, I found that when one animal produced its own signature whistle, its partner was more likely to respond with its own whistle. To better evaluate potential cohesion functions for signature whistles, I then modeled the probability of an animal producing a signature whistle at different times during a temporary separation and reunion from its partner. These data suggest that dolphins use signature whistles to signal a motivation to reunite and to confirm identity prior to rejoining their partner. To examine how cohesion is maintained during separations that do not include whistles, I then investigated whether dolphins could keep track of their partners by passively listening to conspecific echolocation clicks. Using a multi-pronged approach, I demonstrated that the passive detection range of echolocation clicks overlaps with the typical separation ranges of Sarasota mother-calf pairs and that the amount of time since an animal was last able to detect a click from its partner helped explain its probability of producing a signature whistle. Finally, this thesis developed a portable stereo camera system to study cohesion in situations where tagging is not possible. Integrating a GPS receiver, an attitude sensor and 3D stereo photogrammetry, the system rapidly positions multiple animals, grounding behavioral observations in quantitative metrics and characterizing fine-scale changes that might otherwise be missed.
“…GPS errors are well documented, and there are established methods of filtering data for reducing them as much as possible depending on the particular receiver used (e.g., Hide et al 2003;Han and Wang 2012). Pointing errors in direction from the attitude sensor contribute to position error as a function of distance with greater range to target leading to larger errors.…”
Here, we describe a portable stereo camera system that integrates a GPS receiver, an attitude sensor and 3D stereo photogrammetry to rapidly estimate the position of multiple animals in space and time. We demonstrate the performance of the system during a field test by simultaneously tracking the individual positions of six long-finned pilot whales, Globicephala melas. In shore-based accuracy trials, a system with a 50-cm stereo baseline had an average range estimation error of 0.09 m at a 5-m distance increasing up to 3.2 at 50 m. The system is especially useful in field situations where it is necessary to follow groups of animals travelling over relatively long distances and time periods whilst obtaining individual positions with high spatial and temporal resolution (up to 8 Hz). These positions provide quantitative estimates of a variety of key parameters and indicators for behavioural studies such as inter-animal distances, group dispersion, speed and heading. This system can additionally be integrated with other techniques such as archival tags, photo-identification methods or acoustic playback experiments to facilitate fieldwork investigating topics ranging from natural social behaviour to how animals respond to anthropogenic disturbance. By grounding observations in quantitative metrics, the system can characterize fine-scale behaviour or detect changes as a result of disturbance that might otherwise be difficult to observe.
“…The insignificant terms are neglected in the process of linearization (Titterton, 2004). The psi-angle error equations of INS are as follows (Han and Wang, 2012):…”
The integration of Global Positioning Systems (GPS) with Inertial Navigation Systems (INS) has been very actively studied and widely applied for many years. Some sensors and artificial intelligence methods have been applied to handle GPS outages in GPS/INS integrated navigation. However, the integrated system using the above method still results in seriously degraded navigation solutions over long GPS outages. To deal with the problem, this paper presents a GPS/INS/odometer integrated system using a fuzzy neural network (FNN) for land vehicle navigation applications. Provided that the measurement type of GPS and odometer is the same, the topology of a FNN used in a GPS/INS/odometer integrated system is constructed. The information from GPS, odometer and IMU is input into a FNN system for network training during signal availability, while the FNN model receives the observations from IMU and odometer to generate odometer velocity correction to enhance resolution accuracy over long GPS outages. An actual experiment was performed to validate the new algorithm. The results indicate that the proposed method can improve the position, velocity and attitude accuracy of the integrated system, especially the position parameters, over long GPS outages.
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