The pedestrian navigation technologies can be divided into relative positioning and absolute positioning. The inertial navigation system (INS) is commonly used for relative positioning which uses the acceleration and angular rate output by inertial measurement unit (IMU) to integrate to obtain velocity and attitude. INS can provide continuous position without being restricted by external conditions. However, the acceleration and angular rate information both include random noises, which result in integral cumulated errors in velocity and heading [
1]. Fortunately, a zero velocity detection update (ZUPT) technique was proposed to aid the inertial navigation system (INS) [
2,
3,
4], which made the fact that when the pedestrian’s foot is in contact with the ground (still phase), the actual velocity of the foot is zero, and when the still phase is detected, the velocity derived by INS is used as the measured error and then fed to extended Kalman filter (EKF) to estimate the velocity error, called as INS-EKF-ZUPT (IEZ). However, the IEZ algorithm is unable to estimate the error in heading because it cannot obtain the heading observations. Although a zero angular rate update algorithm (ZARU) was proposed to eliminate the error in heading [
5], which is not constrained by the external environment, it had limited ability to correct heading. Heuristic drift elimination (HDE) algorithm [
6] and its variants [
7,
8] were proposed to eliminate heading errors, which are effective in indoor path with linear features. The absolute positioning system GPS is a medium-range circular orbit satellite navigation system which is commonly used for outdoor positioning, navigation, and timing. GPS outdoor positioning technologies include pseudorange-based and carrier phase-based algorithms. Real-time kinematic (RTK) is a carrier phase difference technology which is constructed based on real-time processing of the carrier phase of two stations and that can provide three-dimensional coordinates of the rover in real time using GPS signals. However, under the urban canyon environment, where the satellite navigation signals are blocked by buildings and trees, RTK will fail to achieve high-precision positioning. Seriously, it will result in inability to locate. Therefore, a single positioning method cannot achieve continuous high-precision positioning. GPS integrated with IMU-personal dead reckoning systems (PDR) can be used to solve this problem. Tuan Li, et al. [
9] integrated single-frequency multi-global navigation satellite system (GNSS) RTK with microelectro mechanical systems (MEMS)-IMU tightly coupled for resisting the measurement outliers, which can provide continuous and precision positioning under urban environments. Zun Niu et al. [
10] combined RTK with an IMU-PDR algorithm which used the ZUPT algorithm to assist RTK for the sake of improving positioning performance in urban areas. If the GPS signals are available, RTK is used, if the GPS signals are unavailable, IMU-PDR is used. The integrated navigation algorithms mentioned above are all more robust and allow higher positioning accuracy in complex environments than the signal navigation system. However, there still remain challenges because of the unavailability of GPS signals in indoor environments. To solve this problem, external wireless positioning methods are widely studied to achieve indoor positioning. WiFi and Bluetooth are popular for indoor positioning and have been used for communication because WiFi has become an indoor infrastructure and Bluetooth has lower power consumption and low cost. Besides, both of WiFi and Bluetooth are supported by smartphone. Jingxue Bi et al. [
11] presented an adaptive weighted k-nearest neighbor (KNN) positioning method based on an omnidirectional fingerprint database (ODFD) and twice affinity propagation clustering. Sukhoon Jung et al. [
12] proposed WiFi fingerprint-based approaches following log-distance path loss model for indoor positioning. Devanshi et al. [
13] gave a brief review of indoor localization based on Bluetooth technology. Futoshi Naya et al. [
14] proposed a Bluetooth-based indoor proximity detection method for nursing context awareness. However, WiFi and Bluetooth have low positioning accuracy, which cannot meet the needs of indoor high-precision positioning. The other wireless absolute positioning technologies which can achieve higher positioning accuracy have been studied by some scholars, such as radio frequency identification (RFID) [
15], near field communication (NFC) [
16], ultra wideband (UWB) [
17,
18], and ultrasound [
19]. Antonio Ramón Jiménez Ruiz et al. [
20] presented a tight Kalman Filter (KF)-based INS/RFID integration. André G. Ferreira et al. [
21] proposed a loose-coupled fusion of inertial and UWB. Yuan Xu et al. [
22] presented an improved tightly coupled model of foot-mounted IMU and UWB. Yun Zhuang et al. [
23] integrated INS and PDR in pedestrian navigation applications. However, the coverage of RF-based localization methods works within short distances. Although UWB is a high-precision indoor positioning technology, it is not supported by most smartphones. If UWB is used as the indoor pointing device, we have to use special devices to achieve positioning, which is difficult to promote among consumer users.
Pseudolite is a ground-based transmitter that can transmit signals similar to GNSS [
24], which is supported by the GNSS receiver chip. Therefore, it is meaningful to study indoor positioning based on pseudolite. The pseudolite is composed of a multichannel pseudosatellite host and pseudosatellite antennas. The host modulates multiple navigation signals, and each of navigation signal is transmitted by a pseudolite antenna. The pseudolite deployed in indoor rooms can make up for the shortcomings of GPS signals that cannot reach indoors. However, the multipath effect is more complicated indoors. The integer ambiguity of the carrier phase is difficult to calculate and the pseudolite hardware performance is worse than that of GPS satellites. All of these lead to the low performance of a conventional satellite navigation positioning algorithm. To achieve high-precision positioning, Kenjirou Fujii et al. [
25] proposed hyperbolic positioning with antenna arrays and multichannel pseudolite for indoor localization, which can only achieve high-precision within a small range. Lu Huang et al. [
26] proposed an innovative fingerprint location algorithm for indoor positioning based on array pseudolite, which includes the offline phase and the online phase and needs to collect indoor fingerprints in advance, taking a lot of manpower, and is difficult to maintain. Xingli Gan et al. [
27] presented a Doppler differential positioning technology using the BeiDou system (BDS)/GPS indoor array pseudolite system, which uses the Doppler difference equation and known point initialization (KPI) to determinate the velocity and position of the receiver.
Different from existing works, the RTK/Pseudolite/ landmarks assistance HDE (LAHDE)/IMU-PDR integrated pedestrian navigation system proposed in this paper consists of RTK receiver, pseudolite, manmade landmarks, smartphone, and IMU, which seems unusable in real conditions. However, the GNSS receiver chip in smartphones and the appearance of Android P and the application of BCM47755 chipset make the smartphone Xiaomi Mi 8 possible to use RTK to achieve high-precision positioning. Many domestic and foreign units are engaged in indoor positioning technologies that integrate pseudolite with other technologies, such as 5G [
28] or RFID [
25], and with the dense deployment of 5G and RFID, indoors will be widely covered by pseudolite signals. The Xiaomi Technology Co., Ltd. has developed an IMU embedded in the sole of the shoe [
29], which can be used to achieve pedestrian navigation. There are many manmade parallel and vertical corridors indoors, which can be used to correct the heading derived by an IEZ algorithm. Therefore, only one smartphone and a pair of shoes can implement the proposed system in this paper which is usable in the future. The steps or slope in front of gates (manmade landmarks) or Bluetooth deployed at the corridor entrance can be used to identify whether the pedestrian arrives at an indoor corridor or not, but the scene recognition technologies are not the focus of this study. The main contributions of this paper are summarized below: