Absence Of Location Information Research Articles

Novel High-Precision and High-Robustness Localization Algorithm for Underwater-Environment-Monitoring Wireless Sensor Networks

In marine ecological environment monitoring, the acquisition of node location information is crucial, and the absence of location information can render the collected data meaningless. Compared to the rest of the distance-based localization methods, the received signal strength (RSS)-based localization technique has gained significant interest due to its low cost and the absence of time synchronization. However, the acoustic signal propagates in the complex and changeable aqueous medium, and, in addition to the time-varying path loss factor (PLF), there is often a certain absorption loss, which seriously deteriorates the localization accuracy of the RSS-based technique. To address the above challenges, we propose a novel high-precision and high-robustness localization (NHHL) algorithm that introduces an estimation parameter to conjointly estimate the marine node location and the ambient PLF. Firstly, the original non-convex localization problem is converted into an alternating nonnegative constrained least squares (ANCLS) framework with the unknown PLF and absorption loss, and a two-step localization method based on the primitive dual interior point method and block co-ordinate update method is presented to find the optimal solution. In the first step, the penalty function is utilized to reformulate the localization problem and find an approximate solution. Nevertheless, due to inherent errors, it is unable to approximate the constraint boundary and the global optimum solution. Subsequently, in the second step, the original localization problem is further transformed into a generalized trust region sub-problem (GTRS) framework, and the approximate solution of the interior point method is utilized as the initial estimation, and then iteratively solved by block co-ordinate update to obtain the precise location and PLF conjointly. Furthermore, the closed-form expression of the Cramér–Rao lower bound (CRLB) for the case of the unknown path loss factor and absorption loss is derived to evaluate the our NHHL algorithm. Finally, the simulation results demonstrate the superiority of the presented NHHL algorithm compared with the selected benchmark methods in various marine simulation scenarios.

PistonNet: Object Separating From Background by Attention for Weakly Supervised Ship Detection

Object detection under weakly supervised learning is a challenging issue. In remote sensing ship detection task, the weakly supervised learning method requires that the training set only has image-level class annotations. In the absence of location information, it is difficult to locate ships and extract features. Moreover, when the detector extracts more than one candidate region, the image-level annotation makes it difficult to determine whether the candidate regions are multiple ships or mixed with the detected background. To address these issues, this article analyzes the interaction between class information and location information, and proposes a weakly supervised detection method, PistonNet, based on Data-efficient image Transformers (DeiT). PistonNet proposes an artificial point, which is inserted into the feature map. Artificial point can suppress the background and enhance the object by interfering in the weight distribution of object and background in Self-Attention calculation. PistonNet also proposes joint confidence probability to improve detection accuracy. Experiments on the GF1-LRSD and NWPU VHR-10 dataset show that the proposed method boosts detection performance effectively. The main improvements of PistonNet as well as the contributions of this article are threefold. Firstly, PistonNet is a specific weakly supervised object detection (WSOD) method for single-class detection, which provides an innovative approach to classifying target and background. Secondly, PistonNet reaches the level of advanced supervised detectors on detection accuracy with fewer parameters. Finally, the objects’ locations detected by PistonNet are obtained by segmenting regions on the heatmap. PistonNet’s background suppression ability makes it free from dependence on segmentation threshold.

Translation position extracting in incoherent pattern-illumination Fourier ptychographic photography

Incoherent Pattern-illuminated Fourier ptychography (IFP) is a newly developed super-resolution method, where accurate prior knowledge of translation positions is essential for image reconstruction. To release this limitation, we propose a pre-processing algorithm capable of extracting translation positions of the structure light directly from raw images of IFP, termed translation position extracting (TPE). TPE mainly involves two steps. First, the speckle parts mixed in the acquired raw images, in which the illumination motion is encoded, are isolated by intensity averaging and division. Then the cross-correlations of the speckle dataset are computed to determine the shift positions. TPE-IFP improves the previous IFP by removal of the requirement for prior knowledge of translation positions. Its effectiveness is demonstrated by obtaining high-quality super-resolution images in absence of location information in both simulations and experiments. By further relaxing the practical conditions, the proposed TPE may accelerate the applications of IFP. What's more, as a pre-processing approach, TPE might also contribute to the estimation of pattern positions for the similar speckle-based imaging.

Transmitter Beam Selection in Millimeter-Wave MIMO With In-Band Position-Aiding

Emerging wireless communication systems will be characterized by a tight coupling between communication and positioning. This is particularly apparent in millimeter-wave (mm-wave) communications, where devices use a large number of antennas, and the propagation is well described by geometric channel models. For mm-wave communications, initial access, consisting in the beam selection and alignment of two devices, is challenging and time consuming in the absence of location information. Conversely, accurate positioning relies on high-quality communication links with proper beam alignment. This paper studies this interaction and proposes a new position-aided transmitter beam selection protocol, which considers the problem of joint communication and positioning in scenarios with direct line-of-sight and scattering. Simulation results show significant reductions in latency with respect to a standard protocol.

Energy Efficient Coverage for Mobile Sensor Network

Wireless sensor networks comprise the platform of a broad range of applications related to security system, surveillance, military, health care, and environmental monitoring. The sensor coverage problem has received lots of attention, being considerably driven by recent research in affordable and efficient integrated electronic devices. This problem is centered around a fundamental question: How well do the sensors observe the physical space? The coverage concept is subject to a wide range of interpretations due to a variety of sensors and their applications. Different coverage formulations have been proposed based on the pattern of sensor deployment and type of object to be covered as well as on other sensor network properties such as network connectivity and minimum energy consumption. In this paper, we propose an energy efficient coverage algorithm to extend the sensor network lifetime while maintaining sensing coverage by sensor replacement mechanism. This sensor replacement mechanism manages fault repair in absence of location information. These algorithms keep a small number of active sensor nodes for less energy consumption.

Recycled path routing in mobile ad hoc networks

In mobile ad hoc networks , many routing algorithms rely on some form of flooding to accomplish the route discovery process. Flooding, however, consumes many valuable network resources such as time, bandwidth, and power. Most current routing schemes expire valid routes after a time period to account for nodal movement. This paper proposes a new route discovery method, called recycled path routing (RPR), which directs broadcasts toward the destination node even in the absence of location information. The recycled path routing scheme reduces the search space for the destination node by implementing an expired route cache that is utilized by each node in the network. Routes are added to the expired route cache as they expire from the active route cache and remain there until some time interval has passed or a new route has been discovered. Since these expired routes can provide valuable insight into finding new routes, RPR uses them to direct broadcasts toward the destination node. RPR can save a significant quantity of valuable network resources because only nodes near the optimal path will rebroadcast route requests.