The jellyfish Nemopilema nomurai occupies an important position in the Northwest Pacific ecosystem, and monitoring its biomass is necessary to ensure the protection of fishery resources and the safety of offshore industrial production. The acoustic method has been proposed for jellyfish flux estimation and bloom warning, in which the target strength (TS) of the jellyfish is a crucial parameter. However, varied swimming orientations of jellyfish aggregation result in different backscatter strengths. The acoustic echo characteristics in horizontal swimming orientations and multi-frequency broadband signals are yet to be revealed. This study aims to obtain the TS of jellyfish in various orientations and to comprehensively investigate the jellyfish acoustic echo features at various frequency broadband sounds. In an anechoic tank, we used wide-band echosounder and 70 kHz, 120 kHz, and 200 kHz split-beam transducers to measure the TS of jellyfish swimming omnidirectionally. The results show a difference of approximately 4 dB in the jellyfish’s normalized TS at 70 kHz (frequency range: 45 kHz to 95 kHz) and 200 kHz (frequency range: 160 kHz to 260 kHz) center frequency. The normalized TS of jellyfish varies by around 8 dB between horizontal and vertical swimming orientations. For jellyfish swimming horizontally, the TS and bell diameter have the following least squares fits: ; . The swimming orientation has significant effects on TS estimation and model construction.

In fisheries science research and farmed fish monitoring, acquiring individual fish echoes is the basis for the growth assessment, tracking, and target strength estimation of farmed fish. However, individual fish echo detection methods based on narrowband signal features cannot be applied well to high-density aquaculture scenarios. The broadband signaling system can improve the distance resolution of the detected target and can help to improve the performance of individual fish echo detection. In this study, for the broadband signal system and the characteristics of the underwater fish acoustic echoes, an individual fish echo detection method is proposed using the matched filter output envelope peak interval and instantaneous frequency characteristics of the echo as evaluation indices, and the simulation and experiments of the method are carried out in an anechoic water tank. The results show that the broadband signal system and the corresponding detection method perform better in detecting single target echoes than the narrowband signal system. Compared with the broadband single echo detection method that only relies on the peak interval of the matched filter envelope, the joint detection method that incorporates the instantaneous frequency characteristics of the echo signal has a better rejection capability for overlapping echoes, which can reduce the probability of misjudging the overlapping echoes. The combined detection methods may provide a better detection performance for individual fish echoes.

Obtaining the echo of individual fish is an important prerequisite for fisheries acoustic applications, such as in situ measurement of fish target strength and assessment of fish abundance using the counting method. It is also the foundation for evaluating the growth status of farmed fish and managing aquaculture risks. The density of farmed fish populations is typically higher, and such high-density aquaculture further increases the difficulty of obtaining individual fish echoes in practical applications. Building upon previous research and considering the behavioral characteristics of fish in aquaculture settings, this study conducted performance simulations, live fish experiments in simulated aquaculture cages, and comparative evaluations of three individual fish broadband echo detection methods based on a broadband signal system: the amplitude pulse width method (APM) based on echo envelopes, the peak detection and time delay estimation method (PDM), and the peak time delay combined with instantaneous frequency method (PDIM). This study assumed a dorsolateral fish orientation, which limits its research scope and applicability. The results showed that the PDIM achieved a detection accuracy of 78.34% and a false recognition rate of 1.32%. The APM based on echo envelopes was insensitive to individual fish echoes and had lower recognition accuracy. The PDM exhibited better individual fish echo capture capabilities, while the PDIM demonstrated superior overlapping echo rejection capabilities.

Mechanically scanned sonar can support offshore aquaculture sensing, but acoustic candidate quality and biological identifiability must be evaluated before species modeling. We analyzed 70,421 frames from 22 records and 336 complete rotations acquired on one day in two cages, one per species. A historical top-20-per-rotation detector yielded 6647 candidates, of which 4801 passed morphology rules; an uncapped rerun yielded 27,980 candidates and 14,402 passes. The 5 m between-cage pass-fraction gap fell from 26.9 to 0.4 percentage points after uncapping, revealing selection amplification. A separate probability sample of 128 passes, failures, and lower-ranked candidates yielded 83.6% agreement (κ = 0.627) between two blinded reviewers. Rater-specific, sampling-weighted proportions of automatic passes judged visually isolated were 39.2% and 55.3%; these labels do not establish single-fish identity. In the historical capped 142-case matched cohort, the mixed acoustic/detector set showed a record-level domain association (balanced accuracy 0.919; six-test Holm-adjusted p = 0.0030), conditional on ranking and selection. Species effects cannot be separated from cage effects in this one-cage-per-species design. This case study audits design eligibility, candidate selection, and reviewer dependence before biological classifier development.