Detection of bearing-only trajectory of multi-target using Hidden Markov model

Xin, Jirong; Zhao, Yan; Luo, Laiyuan

doi:10.1109/icmic.2017.8321564

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2024

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“…Therefore, it is necessary to estimate the state of the target at each moment in order to achieve energy focusing with accumulation of signal power spectrum along trajectory point. In reference [7], a HMM is established to extract the target azimuth trajectory in the Bearing-Time Recording (BTR) obtained for a certain bandwidth signal. A hidden Markov model is established on the omnidirectional LOFAR spectrum to estimate the frequency time series of the target signal in reference [8].…”

Section: Introductionmentioning

confidence: 99%

Line spectrum detection and motion parameters estimation for underwater moving target

Shi,

Piao,

Guo

2024

J. Phys.: Conf. Ser.

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For the detection of underwater moving target with constant speed at low signal-to-noise ratio (SNR), a track-before-detect method is proposed based on motion parameters estimation and hidden Markov model (HMM). Optimization algorithm is used for the moving target motion parameter estimation with cost function obtained by energy accumulation along line spectrum tracked with 1-D Hidden Markov model in spatially filtered LOFAR spectrum. This method is suitable for detecting weak targets with fast changes in azimuth.

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Section: Introductionmentioning

confidence: 99%