For the problem of the detection and tracking about multiple maneuvering fluctuating weak targets in radar systems, a track-before-detect algorithm based on interactive multi-model multi-Bernoulli filtering (IMM-MBTBD) is proposed. In a track-before-detect algorithm, the squared modulus likelihood ratio (SLR) is usually utilized to match the possible trajectories of targets. In this method, however, only the amplitude information is considered and the phase information is ignored, which leads to a decrease in filter performance. In this paper, we use the complex likelihood ratio (CLR) instead of the SLR in the IMM-MB-TBD and preserve the spatial coherence of the phase to realize the detection and tracking about multiple amplitude fluctuation targets with the Swerling 0,1, and 3 fluctuations. Furthermore, in order to accommodate to the situation where the prior information of target births is unknown and overcome the difficulty of detecting a weaker target and a stronger target at the same time when the targets fluctuate, an adaptive birth algorithm based on measurement likelihood ratio is proposed. Simulation results show that at low signal-to-noise ratio, the proposed IMM-MBTBD algorithm provides better performance in estimating of the state and number of targets.
KEYWORDS: Detection and tracking algorithms, Particles, Particle filters, Electronic filtering, Signal to noise ratio, Optical filters, Monte Carlo methods, Computer simulations, Algorithms, Picosecond phenomena
Aiming at the problem of Direction of Arrival (DOA) tracking for multiple target, this paper proposes a DOA tracking algorithm based on Propagator Method (PM) under Multi-Bernoulli filtering framework. The proposed algorithm uses particle filter to approximate the posterior distribution of target, where the calculation of likelihood function is the key of the update step. The eigendecomposition of the covariance matrix is needed when the likelihood function is replaced by MUSIC spatial spectrum function. In order to reduce the computational complexity of the matrix eigendecomposition, we use the spatial spectral function of PM to replace the pseudo-likelihood function of particle filter, and further exponential weighting is used to enhance the weight of particles at high likelihood area and make resampling more efficient. The simulation results show that the proposed algorithm can effectively track the DOA and estimate the number of multiple maneuvering target.
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