School of Zoology, Tel Aviv University, Tel Aviv 69978, Israel.
The Alexander Silberman Institute of Life Science, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.
Sensors (Basel). 2023 Nov 28;23(23):9460. doi: 10.3390/s23239460.
Time-of-arrival transmitter localization systems, which use measurements from an array of sensors to estimate the location of a radio or acoustic emitter, are now widely used for tracking wildlife. Outlier measurements can severely corrupt estimated locations. This article describes a new suite of location estimation algorithms for such systems. The new algorithms detect and discard outlier time-of-arrival observations, which can be caused by non-line-of-sight propagation, radio interference, clock glitches, or an overestimation of the signal-to-noise ratio. The new algorithms also detect cases in which two locations are equally consistent with measurements and can usually select the correct one. The new algorithms can also infer approximate altitude information from a digital elevation map to improve location estimates close to one of the sensors. Finally, the new algorithms approximate the covariance matrix of location estimates in a simpler and more reliable way than the baseline algorithm. Extensive testing on real-world data involving mobile transmitters attached to wild animals demonstrates the efficacy of the new algorithms. Performance testing also shows that the new algorithms are fast and that they can easily cope with high-throughput real-time loads.
到达时间发射机定位系统利用传感器阵列的测量值来估计无线电或声发射源的位置,现已广泛用于野生动物追踪。异常值测量值可能严重破坏估计位置。本文介绍了这种系统的一套新的定位估计算法。新算法可以检测和丢弃异常的到达时间观测值,这些异常值可能是由非视距传播、无线电干扰、时钟故障或信噪比估计过高引起的。新算法还可以检测到两个位置与测量值一致的情况,通常可以选择正确的位置。新算法还可以从数字高程图中推断出近似的海拔信息,以改善接近传感器之一的位置估计。最后,新算法以比基线算法更简单、更可靠的方式近似位置估计的协方差矩阵。在涉及附着在野生动物身上的移动发射机的真实世界数据上的广泛测试证明了新算法的有效性。性能测试还表明,新算法速度快,能够轻松应对高吞吐量的实时负载。