Applying an Adaptive Signal Identification Method to Improve Vessel Echo Detection and Tracking for SeaSonde HF Radar

To enhance remote sensing for maritime safety and security, various sensors need to be integrated into a centralized maritime surveillance system (MSS). High-frequency (HF) radar systems are a type of mainstream technology widely used in international marine remote sensing and have great potential to detect distant sea surface targets due to their over-the-horizon (OTH) capability. However, effectively recognizing targets in spectra with intrinsic strong disturbance echoes and random environmental noise is still challenging. To avoid the above problem, this paper proposes an adaptive signal identification method to detect target signals based on a rapid and flexible threshold. By integrating a watershed segmentation algorithm, the subsequent direction result can be used to automatically compute the direction of arrival (DOA) of the targets. To assist in the orientation of the object, forward intersections are integrated with the technique. Hence, the proposed technique can effectively recognize vessel echoes with automatic identification system (AIS) verification. Experiments have demonstrated the promising feasibility of the proposed method’s performance.

Comparing Echo-Detection and Echo-Localization in Sighted Individuals

Echolocation is the ability to gather information from sound reflections. Most previous studies have focused on the ability to detect sound reflections, others on the ability to localize sound reflections, but no previous study has compared the two abilities in the same individuals. Our study compared echo-detection (reflecting object present or not?) and echo-localization (reflecting object to the left or right?) in 10 inexperienced sighted participants across 10 distances (1–4.25 m) to the reflecting object, using an automated system for studying human echolocation. There were substantial individual differences, particularly in the performance on the echo-localization task. However, most participants performed better on the detection than the localization task, in particular at the closest distances (1 and 1.7 m), illustrating that it sometimes may be hard to perceive whether an audible reflection came from the left or right.

Increased emission intensity can compensate for the presence of noise in human click-based echolocation

Echolocating bats adapt their emissions to succeed in noisy environments. In the present study we investigated if echolocating humans can detect a sound-reflecting surface in the presence of noise and if intensity of echolocation emissions (i.e. clicks) changes in a systematic pattern. We tested people who were blind and had experience in echolocation, as well as blind and sighted people who had no experience in echolocation prior to the study. We used an echo-detection paradigm where participants listened to binaural recordings of echolocation sounds (i.e. they did not make their own click emissions), and where intensity of emissions and echoes changed adaptively based on participant performance (intensity of echoes was yoked to intensity of emissions). We found that emission intensity had to systematically increase to compensate for weaker echoes relative to background noise. In fact, emission intensity increased so that spectral power of echoes exceeded spectral power of noise by 12 dB in 4-kHz and 5-kHz frequency bands. The effects were the same across all participant groups, suggesting that this effect occurs independently of long-time experience with echolocation. Our findings demonstrate for the first time that people can echolocate in the presence of noise and suggest that one potential strategy to deal with noise is to increase emission intensity to maintain signal-to-noise ratio of certain spectral components of the echoes.