Study On PF-TBD Algorithm And Application For The Skywave Othr

As a result of signal-to-noise ratio and signal-to-clutter ratio reduction in complexmodern warfare circumstance, conventional detecting methods are hard to detect targeteffectively. It is necessary to develop a novel detecting and tracking method for weaktargets. Instead of directly setting threshold to observation data, TBD detect aftermulti-frame accumulation by a certain decision rule. The track is declared meanwhilethe target is detected. Particle filter is a Bayesian recursive filtering algorithm, moreoverthe likelihood ratio can be constructed by the weights of particles. These make itpossible that particle filter can fulfill the duties of detection and tracking entirely. TheTBD algorithm based on particle filter is one of the most important TBD algorithms.The thesis focuses on the studies of the PF-TBD algorithm using different models.It mainly comprises:1. Two PF-TBD algorithms based on existence probability, namely the StandardPF-TBD algorithm and the Efficient PF-TBD algorithm are studied and compared. Thesimulations show that the detection performance of Efficient PF-TBD algorithm issuperior to the Standard PF-TBD algorithm under the high and middle signal-to-noiseratio, oppositely under the low one, at the detection threshold of0.5and0.6. Theaverage false alarm probability of the former exceeds the latter.2. For solving the problem that the PF-TBD algorithm based on sequentialprobability ratio test(SPRT) is unable to detect the disappearance of the target, a newmodified approach which the single-moment likelihood ratios are used for slidingwindow processing, is proposed. Existence of target is decided if the likelihood ratios ofthe sliding window surpass the threshold. Inexistence of target else if the likelihoodratios are under the threshold. Or else the last decision continues. This algorithm solvedthe problem of detecting the disappearance of the target effectively, and enhance thedetection probability in lower SNR compared with PF-TBD algorithm based on SPRT.3. PF-TBD algorithms are compared，the average effective detection probability ofthe Standard PF-TBD algorithm is higher above certain SNR than the Efficient PF-TBDalgorithm, the Efficient PF-TBD algorithm is lower on the average false alarm probability, and both can detect the appearance and disappearance effectively. PF-TBDalgorithm based on modified single-moment likelihood ratio can detect thedisappearance effectively that PF-TBD based on SPRT cannot.4. PF-TBD algorithm is applied to skywave OTH radar model, which generatesobservation data by means of matched filtering, fast Fourier transforming and beamforming to echoes and the data can be applied for TBD. Afterwards the data is processedby the Standard PF-TBD algorithm and detection for weak targets based on OTHR isimplemented. The effectiveness is confirmed by simulations.