Signal comparison-based Location Determination

Explore the various applications used by Signal comparison technique for location determination. See the role of Artificial Intelligence as well as Machine Learning in helping to improve the existing technique and quality of service delivery, making it essential to choose the most appropriate signal for location determination.

Introduction

Signal comparison-based location determination is a technique for determining the location of an object or a person. It works by comparing the strength of signals from different sources and selecting the area based on the difference in signal strength.

The fundamental principle of signal strength-based location determination is that the received signal strength indicator (RSSI) at a receiver is a function of the transmitter's location.

Applications of Signal Comparison-based Location Determination

Global Positioning System (GPS) is one of the most used navigation systems. It applies this technique by using signals from a network of satellites orbiting the Earth to determine a device's location. As the device picks up signals from different satellites, it compares their strength and uses the information to determine its location.

The Assisted Global Positioning System (A-GPS) comes into play when the received signal is either noisy or distorted by multipath fading and can reliably be used for ranging operations in many cellular environments. The cellular service provider allows additional GPS information to be sent to the Mobile Station (MS) as an additional message when positioning location information is requested.

The fingerprint Method can be used for indoor places or where GPS cannot function as required. There are two steps for this method:
- Off-line step
- On-line step

The off-line Step is where, at each specific position, the signal strength is collected to create a radio map for matching based on the relationship between signal strength and position during the online step.

The In-line Step is where the positioning location techniques compute the Received Strength Signal (RSS) in real-time and measure the estimated location coordinated based on the information stored during the off-line step. The received Strength Signal (RSS) method can provide no additional hardware installation in both network and target nodes, and it has high accuracy in short-range and Line-of-Sight (LOS) environments. Secondly, it does not require time synchronization between the nodes in the system, unlike the Time of Arrival (TOA) method.

It is important to keep updating the radio map frequently to accommodate new changes in the radio coverage, which improves the accuracy of the measurements.

Enhanced Observed Time Difference (E-OTD) is another method to determine the position location of the user’s mobile station (MS) in the cellular network. It measures the TOA of signals from multiple base stations at the MS. The time difference between the signal arrivals from different base stations is utilized to conclude the user’s position location concerning the base stations, provided that the base stations ’ coordinates are known and they send time-synchronized signals. Base stations (BS) are typically synchronized using fixed GPS receivers. E-OTD does have a major advantage over simple GPS in that it works indoors and in overcast weather conditions; thus, it increases the cost for wireless service providers.
Wi-Fi Positioning is another technique for detecting and tracking the location of people, devices, and assets. It can also be activated easily for indoor positioning with existing Wi-Fi access points (APs), Wi-Fi-enabled sensors, and hotspots. The measure taken by Wi-Fi positioning is called the Received Signal Strength Indicator (RSSI).

In RSSI-based applications, the multiple existing Wi-Fi access points or Wi-Fi-enabled sensors deployed in a fixed position will detect transmitting Wi-Fi devices and the received signal strength of the signal from the device. The location information gathered by access points (APs) or sensors is sent to the central indoor positioning system (IPS) or real-time location system (RTLS). The location engine analyzes the data and uses multilateration algorithms to estimate transmitting device locations.

WLAN positioning location is a way of locating mobile devices, such as laptops that use the Received Strength Signal (RSS) method. Algorithms in the central site of existing WLANs are permitted without the need for additional hardware. Positioning location is carried out by utilizing the dependency between the location of a mobile device (MD) and the signal transmitted between the MD and a set of WLAN access points.

Advantages of Signal comparison-based location determination

It is a cost-effective solution for location determination.
There is no requirement for additional hardware, and no processing is needed for the system to acquire location determination.

Artificial Intelligence and Machine Learning roles in Signal-based Location determination

Regarding improving accuracy and speed, Artificial Intelligence (AI) can play an important role in Signal-based Location determination. Helping in applications such as localization, smart signaling, and environmental sensing. Artificial Intelligence (AI) enables RF (Radio Frequency) Sensing, where there is a difference between in Active Positioning and Passive Positioning. Active Positioning is used mostly indoors and in other locations without clear sight of the Global Navigation Satellite System (GNSS). Applications of active positioning with RF sensing include vehicular navigation and indoor navigation.

Qualcomm Technologies has recently developed the Snapdragon X70 5G modem-RF system, which requires domain knowledge of both wireless and Machine Learning (ML). Machine Learning enables RF sensing by using self-supervised learning for active positioning and unsupervised learning for RF sensing and passive positioning. Machine learning uses generative modeling for channel representation and simulation to improve communication.

Top IP Holders in Signal comparison-based Location Determination

The following are the ten major players with a significant patent portfolio in Live Streaming and gaming technologies:

Fig .5 shows the major technology domain involved in Signal comparison-based Location determination by these market leaders.

Conclusion

It can be said that signal comparison-based location determination is a reliable and accurate method for locating objects or individuals from the field of navigation to indoor localization. The effectiveness of this technique lies in its ability to compare the signals from different antennas and triangulate the target's location accurately. With the advancement of technology, the signal comparison-based location determination method has been optimized further to provide real-time location updates with improved accuracy. Looking into the future, with the increasing demand for location-based services, signal comparison-based location determination is a promising solution that will continue to be used and developed in various industries.

Disclaimer: This report is based on information that is publicly available and is considered to be reliable. However, Lumenci cannot be held responsible for the accuracy or reliability of this data.