TY - JOUR
T1 - Inertial-navigation-aided single-satellite highly dynamic positioning algorithm
AU - Zhang, Lingling
AU - Tang, Chengkai
AU - Zhang, Yi
AU - Song, Houbing
N1 - Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - Nowadays, research on global navigation satellite systems (GNSS) has reached a certain level of maturity to provide high-precision positioning services in many applications. Nonetheless, there are challenging GNSS-denial environments where a temporarily deployed single-satellite positioning system is a promising choice. To further meet the emergency call of highly dynamic targets in such situations, an augmented single-satellite positioning algorithm is proposed in this paper. First, the initial location of the highly dynamic target is found by real-time displacement feedback from the inertial navigation system (INS). Then, considering the continuity of position change, and taking advantage of the high accuracy and robustness of the unscented Kalman filter (UKF), target location is through iteration and fusion. Comparing this proposed method with the least-squares Newton-iterative Doppler single-satellite positioning system and the pseudorange rate-assisted method under synthetic error conditions, the positioning error of our algorithm was 10% less than the other two algorithms. This verified the validation of our algorithm in the single-satellite system with highly dynamic targets.
AB - Nowadays, research on global navigation satellite systems (GNSS) has reached a certain level of maturity to provide high-precision positioning services in many applications. Nonetheless, there are challenging GNSS-denial environments where a temporarily deployed single-satellite positioning system is a promising choice. To further meet the emergency call of highly dynamic targets in such situations, an augmented single-satellite positioning algorithm is proposed in this paper. First, the initial location of the highly dynamic target is found by real-time displacement feedback from the inertial navigation system (INS). Then, considering the continuity of position change, and taking advantage of the high accuracy and robustness of the unscented Kalman filter (UKF), target location is through iteration and fusion. Comparing this proposed method with the least-squares Newton-iterative Doppler single-satellite positioning system and the pseudorange rate-assisted method under synthetic error conditions, the positioning error of our algorithm was 10% less than the other two algorithms. This verified the validation of our algorithm in the single-satellite system with highly dynamic targets.
KW - Highly dynamic positioning
KW - Inertial navigation system (INS)
KW - Pseudorange difference
KW - Single-satellite system
KW - Unscented kalman filter (UKF)
UR - http://www.scopus.com/inward/record.url?scp=85072775327&partnerID=8YFLogxK
U2 - 10.3390/s19194196
DO - 10.3390/s19194196
M3 - 文章
C2 - 31569707
AN - SCOPUS:85072775327
SN - 1424-8220
VL - 19
JO - Sensors
JF - Sensors
IS - 19
M1 - 4196
ER -