## 2 Related Work  
In 2002, the U.S. Federal Communications Commission allowed UWB carrier frequencies of 3.1-10.6 GHz for civil communication usage. The ratio of the \(-10\) dB bandwidth to the system center frequency is larger than 20%, and the system bandwidth is at least 500 MHz [13]. The corresponding transmission power spectral density is less than \(-41.25\) dBm\(W\)/MHz. Gaussian pulse waveforms are often used in UWB systems because they are easy to generate [14]. In the last decade of the 20 th century, emerging ultra-wide-band (UWB) impulse technology was used in numerous applications in the commercial as well as the military sectors [15]. Table 1 lists the main methods in UWB positioning technology in the past decade undertaking various improved algorithms to improve positioning accuracy. [PERSON] et al. [16] explored the use of cross-correlation-based TDOA methods in conjunction with a novel technique for combining the TDOA estimates from multiple antenna pairs to build an estimate of the transmitter position. [PERSON] et al. [17] proposed a distributed localization scheme for nodes with emphasis on power measurements (RSSI) using UWB. The localization algorithm was distributed and followed an indirect approach where nodes determine their location with the help of their neighbors. [PERSON] et al. [18] applied an improved TDOA method to achieve UWB localization in the mobile environment. The ETDGE algorithm for ranging and the Fang iterative algorithm for locating the moving node were approached in an optimum manner. In practice, the positioning accuracy of UWB systems always faces positioning error challenges caused by disturbance factors from ME, NLOSI, and AI. In the past decade, scholars proposed different error measurement algorithms and error elimination methods to address this issue. Typically, [PERSON] et al. [19] studied the joint TOA and AOA statistics of indoor UWB propagation channels, proposing an iterative UWB channel characterization algorithm, and the path loss characteristics of indoor UWB were studied using a Hermite polynomial model to simulate the received signals. [PERSON] et al. [20] studied the path loss characteristics of indoor UWB systems using the spatial smoothing MUSIC algorithm to test the azimuth and elevation arrival angles of multipath signal challenges, determining that multipath reflection in small rooms was significantly higher than that in large rooms. [PERSON] et al. [21] proposed a multipath-assisted deviceless localization system with amplitude and phase information that calculated the influence on the received signal based on the position of the person in the target area. [PERSON] et al. [22] proposed a practical NLOS recognition technique, including a reduction factor to reduce the severe impact of NLOS situations and a set of appropriate features to improve the speed of NLOS recognition. [PERSON] [23] considered the AOA based on the Saleh-Valenzuela model and verified the effectiveness of using a spectrum to overcome the ME. [PERSON] et al. [24] studied a new modeling method for parameter estimation of low-level multipath structures in UWB indoor communication channels. This method reduced the lack of transparency in the entire parameter estimation process and optimized the performance evaluation of the UWB physical layer scheme. [PERSON] et al. [25] proposed a proportional adaptive technology to alleviate the multipath fading effect in advanced wireless communication systems. [PERSON] et al. [26] proposed a multipath map based on the principle of spatial domain modeling. [PERSON] et al. [27] adopted a beam-guided circularly polarized antenna to suppress indoor multipath propagation. [PERSON] et al. [28] put forward an indoor positioning system (IPS) combining inertial measurement unit (IMU) and UWB, which improved the robustness and accuracy of the system through extended Kalman filter (EKF) and unscented Kalman filter (UKF). [PERSON] et al.