# Review of Indoor Positioning: Radio Wave Technology
## 1 Introduction
The transmission data can be obtained via light beams as the light pulses and these receiving data change with distance. The authors in [15] performed a comprehensive survey of VLC innovation by applying LED light bulbs. VLC has been intended to replace the usage of other radio frequency areas, as a more efficient and commercially orientated high bandwidth transmission but requires higher hardware complexity [16]. For computer vision and image processing, adequate illumination from the light source can support the camera to detect the location of things successfully. Consequently, the camera-based location determinations are dependent on the lighting condition. Sound technologies (ultra- or audible sound) have constraints within the 20 Hz to 20 kHz range of audio frequency. Human ears are able to absorb acoustic intensity in environments. A microphone or speaker could be used to generate the electrical signals converted from sound signals through transducers. Sound detection sensors, microphone sensors and ultrasonic sensors are commercially used to detect the intensity of sound. Subsequently, an ultrasonic sensor is used as a distance sensor by first estimating the time taken in traveling the sound signal between the source and sensor. Echo and trigger pins of ultrasonic sensor work as a transmitter and receiver during this work. Therefore, for indoor tracking purposes, an ultrasonic sensor is used as a distance-based device in an ultrasonic location detection system [17]. Signal-based distance measurement techniques, time of arrival (TOA) and time difference on arrival (TDOA) can be used to measure time for distance estimation. However, ultrasound signals cannot penetrate well through an obstruction. Thus, it is inappropriate for sensing in wide-ranging locations; hence, sound technology is not prevalent in indoor localization appliances. In recent times, modern smartphones are composed of compatible sensors for specialty functions. Smartphone sensors are capable of collecting data based on the relative human motion by means of the estimated position is provided by the embedded sensors. More precisely, an accelerometer, gyroscope, proximity sensor, magnetometer, and pedometer inside a mobile phone are viable for the tracking and navigation system. Considering for indoor positioning system, magnetic field measurement and an inertial navigation system could determine the location problem in the coverage area. A magnetic field (inertial technology) uses the magnetometer to measure the magnetic field variations as well as to support the position estimation of a person or object. Magnetic field data are used for pedestrian dead reckoning (PDR) application [18,19]. In [18], the system is integrated into the long period operation and coarse indoor ambience that is based on the walking prolongation of approximately 1390 m and the operating time 45 min. However, the magnetic positioning system (MPS) is not intended for accuracy. In [19], the author proposed the positioning and calibration algorithms of indoor MPS and then the impressive positioning accuracy computed in a real indoor environment. An argument in favour of magnetic signatures is that it can infiltrate extensively in obstructed materials and can operate the endeavours of non-line-of sight (NLoS) propagation. INS is a navigation device, typically used for manned and unmanned aerial vehicles, underwater vehicles and mobile robot applications. MEMS have low-cost sensors and inertial measurement units (IMUs) sensors that can help capture the human movement direction and angular speed. This brings the positioning solution of PDR that the multiplicity of smartphone built-in sensors can detect the footstep length counting, the speed of human movements and rotation. It is also a GPS aided device [20,21]. The frequent criticism of smartphone built-in sensors is that the motion estimated errors and time-invariant process have occurred in a comparative study of radio signal attractiveness.