Improving Positioning Accuracy Using Optimization Approaches: A Survey, Research Challenges and Future Perspectives

The current onboard wireless and sensors technologies have a significant role in improving day-to-day users' activities. Examples of these technologies are WiFi, Bluetooth, Cellular, Global Navigation Satellite System (GNSS), proximity, camera, and inertial sensors. Using these technologies provides many applications from the range of communication to the location-based systems (LBS). The LBSs locate people and objects from outdoors into indoors for many purposes, including navigation, entertainment services, and even for security issues. However, the most notable limitations of these technologies include a lack of accuracy and cost-efficiency. Several research types have been attempted to tackle these issues by combining the various technologies, using smart models, and applying optimization algorithms. Therefore, this study reviews many models on the shelf and analyzes the models according to their improvement of accuracy, reduction of time to fix, and cost-efficiency. Specifically, in this study, the optimization algorithms used for positioning purposes are investigated and classified into two groups of algorithms: statistical and non-statistical algorithms. Further, the study also illustrates the weaknesses and limitations of the surveyed algorithms. Finally, the famous challenges and future trends are listed to provide a useful guide for the current readers.