Multistatic Moving Object Localization by a Moving Transmitter of Unknown Location and Offset

Zhang, Yang; Ho, K. C.

doi:10.1109/tsp.2020.3008752

Cited by 38 publications

(1 citation statement)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CRLB for direct path and indirect measurements are derived from the multistatic localization of sensors. [32][33][34] The indirect path measurements are estimating the position of non-cooperative moving target in the presence of measurement noise, vortex-induced vibrations. The quality of indirect path measurements decreases when the error covariance matrix increases.…”

Section: Crlb For Direct and Indirect Pathmentioning

confidence: 99%

Vortex‐induced vibration effects in underwater acoustic wireless sensor networks

Reddy,

Arya

2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

A randomly fluctuated vortex‐induced vibration (VIV) affects the localization of moving targets in an underwater acoustic wireless sensor network (UAWSN) to cause an offset time and time synchronization error which disturbs the localization of the non‐cooperative moving target. Definition 1, Theorem 1 has been introduced in the present work to describe the genesis and consequences of the VIV effect in UAWSN. An elliptic localization introduces the direct and indirect path measurements of the moving target. The standard Crammer Rao lower bound parameter quantifies the VIV effect. The compensation of vortex‐induced vibrations (CVV) algorithm is proposed to quantify the degradation of localization performance and to estimate the position of the moving target. The theoretical measurements of position error, velocity error with respect to the variation of noise, number of receiver sensors, and probability of line of sight errors are compared to the standard methods. The proposed CVV algorithm improves the localization performance by 32.24% and reduces 34.36% of position errors, and 37.46% of velocity errors up to 600 m. It can be useful for the sub‐aquatic internet of underwater things.

show abstract

Section: Crlb For Direct and Indirect Pathmentioning

confidence: 99%