Abstract The trajectory localisation of human activities using signal analytics has become a reality due to the widespread use advanced processing systems. Device‐free WiFi devices is prevalent, and received strength indicator (RSSI) channel state information (CSI) signals offer additional benefits. However, radio frequency (RF) highly dependent on environment, so updating fingerprint data nece...

The fingerprint technique is used as an indoor localization method. This study uses a CNN-based estimation accuracy of CNN improves the number AP information (AP identifiers and received signal strength indicator) increases. However, gathering time-consuming costly. problem can be solved using UD users measured). measuring method does not know user’s exact location. Therefore, it essential to c...

Because the received signal strength indicator (RSSI) value greatly changes, the direct use of RSSI value has more errors in the positioning process as the basis to calculate the position of anchor nodes. This paper proposes a RSSI node localization algorithm based on constraint particle swarm optimization (PSO-RSSI). In the algorithm, particle swarm optimization is used to select anchor nodes ...

This paper considers a scenario in which signals from an emitter at an unknown location are received at a number of different collinear locations. The receiver can determine the received signal strength, but no other parameters of the signal. Postulating a log-normal transmission model with a constant but unknown path loss exponent and, also, an unknown transmit power and known noise variance, ...

Solutions for indoor localization have become more critical with recent advancement in context and location-aware technologies. When wireless sensor network (WSN) used in complex indoor environment, great propagation loss will be caused and it is very difficult to estimate adaptively the location of target nodes when environment changed. In this paper, an indoor adaptive localization algorithm ...