Accurate DOA Estimation With Adjacent Angle Power Difference for Indoor Localization

Abstract

Indoor localization with high accuracy plays a key role in the field of Internet of Things in 5th-Generation (5G) era. With the introduction of Multiple Input Multiple Output (MIMO) technology in 5G, the direction-of-arrival (DOA) method is highly feasible in indoor localization. However, the direction of arrival is susceptible to complex indoor environment. To improve the accuracy and stability of DOA estimation, an adjacent angle power difference (AAPD) method is proposed based on Orthogonal Matching Pursuit (OMP). This method uses OMP to obtain an initial estimate of the direction, and then, adjusts the estimation by calculating the difference power of adjacent points at initial value point to get the fractional DOA. In the scenario of continuous movement, beamforming is further applied, which reduces the amount of calculation. Both simulation and experimental results show that the proposed method can achieve high accuracy and eliminate the error jitter. Compared with the classical Multiple Signal Classification (MUSIC) method for DOA estimation, the proposed method can increase accuracy by 46% under the condition of low SNR (Signal-to-Noise Ratio). The probability that the measurement error does not exceed 5 • in the actual movement tests is 97.5%.

Decimeter Level Indoor Localization Using WiFi Channel State Information

“…The height of the APs and transmitters is identical and ground truth location and orientation were confirmed by using laser rangefinders, building protractors, and geometric relationships between transmitter and receiver. In our experiments, the proposed 2D M-MP method is compared to some previous works, which are based on the 2D MUSIC algorithm [1], [9], [15], original 2D MP algorithm [10], [12] and 2D OMP algorithm [30], [32]- [33] for evaluating the parameter estimation accuracy and localization accuracy. Due to the lack of synchronization between transmitter and receiver, ToF is not available, so we only evaluate AoA accuracy and use triangulation for localization.…”

Integrity Monitoring for Bluetooth Low Energy Beacons RSSI Based Indoor Positioning

“…The HAL is given according to the actual application requirements，therefore, whether IM is available or not can be judged according to the following criteria: � HPL < HAL: Available HPL ≥ HAL: Unavailable (33) when the HPL is greater than or equal to the HAL, the IM algorithm is unavailable and the user should be alarmed in time.…”

“…This paper is based on the RSSI methods. The geometric methods like Time of Arrival (TOA) [31], [32], Angle of Arrival (AOA) [33], and Time Difference of Arrival (TDOA) requiring specialized hardware, which is costlier than RSSI methods [34]. The RSSI based positioning methods commonly used can be divided into range-free methods and range-based methods [35], a classic range-free method based on RSSI is the fingerprinting positioning method as in [26,28].…”

Signal acquisition of Luojia-1A low earth orbit navigation augmentation system with software defined receiver

“…Many studies consider using Signals of Opportunity (SOP) for positioning when GNSS is unavailable or unreliable. These SOP include digital television (Chen et al 2017b;Chen et al 2014), Bluetooth (Cao et al 2019), LEO (Chen, Wang, and Zhang 2016;Ardito et al 2019), Wi-Fi (Yan et al 2021(Yan et al , 2018(Yan et al , 2017, vision (Wang et al 2020;Chen et al 2017), and 5 G (Dammann, Raulefs, and Zhang 2015;Wymeersch et al 2017;Zhou et al 2020), and so on. Among them, the LEO satellite has been paid more and more attention and has become a research hotspot.…”