Abstract
Aimed at the problem of detecting maneuvering targets in the Gaussian and sea clutter environments and based on the established motion state model, this paper proposed a new scheme that uses a joint radar-communication (JRC) system with Kalman filter to accurately detect the target with the generalized likelihood ratio test (GLRT) theory and a constant false alarm rate (CFAR) based threshold. Also, the theoretical threshold and probability function of GLRT target detection based on CFAR were given. Moreover, target detection probability of the new JRC system in Weibull andKdistribution clutter is deduced. In addition to theoretical considerations, simulations and measurement results of the new JRC systems demonstrate excellent detection performance for maneuvering targets in the Weibull andKdistribution channel.
Highlights
In recent years, maneuvering target detection problem has attracted substantial interest, which is very meaningful for modern radars to improve their detection performance [1,2,3,4]
Aimed at the problem of detecting maneuvering targets in the Gaussian and sea clutter environments and based on the established motion state model, this paper proposed a new scheme that uses a joint radar-communication (JRC) system with Kalman filter to accurately detect the target with the generalized likelihood ratio test (GLRT) theory and a constant false alarm rate (CFAR) based threshold
(5) Based on the established motion state model, the joint radar-communications (JRC) system with Kalman filter accurately detects the target with GLRT theory and sets the detection threshold based on CFAR
Summary
In recent years, maneuvering target detection problem has attracted substantial interest, which is very meaningful for modern radars to improve their detection performance [1,2,3,4]. The above four kinds of targets can be summarized as “far-range, low-observable, and highly maneuvering” targets They share a lot in common that, both in time and in frequency domain, the SCR/SNR is too low to compete with clutter and electronic interference, resulting in poor detection performance [5, 6]. It has been found that the spiky clutter returns can be suitably modeled by a multidimensional Gaussian mixture distribution or a spherically invariant random vector (SIRV) [12]. Aimed at the problem of detecting maneuvering targets with high speed in sea clutter and based on the established motion state model, the JRC system with Kalman filter accurately detects the target with GLRT theory and sets the detection threshold.
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