It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model (MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter, the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect (TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.
Joint detection and tracking weak target is a challenging problem whose complexity is intensified when there are multiple targets present at the same time. Some Probability Hypothesis Density (PHD) based track-before-detect (TBD) particle filters (PHD-TBD) are proposed to solve this issue; however, the performance is unsatisfactory especially when the number of targets is large because some assumptions in PHD are violated. We propose to modify the general PHD-TBD filter in two aspects to make the PHD processing available for TBD scenarios. First, the distribution of false alarms is approximated as the Poisson distribution through a threshold method, and then a clustering technique is proposed to solve the overestimation of the target number. A typical TBD scenario is used to test the effectiveness of the proposed method. Simulation results indicate that the proposed method outperforms the general method in terms of estimation accuracy and computational complexity.INDEX TERMS Multitarget tracking, track-before-detect (TBD), particle filter, probability hypothesis density (PHD).
Based on time-reversal (TR) technique, the model of single frequency spatial power combining using sparse array is established. The efficiency function of spatial power combining is defined. The expression for the relationship of the statistical characteristics of combining efficiency at the time of maximum amplitude with the phase error and the number of array elements is derived. The analysis shows that when other parameters are determined, if the phase errors of the array nodes are mutually independent, and obey the uniform distribution to a certain extent, the combing efficiency's mean would not be related to the number of array elements N, but related to the statistic parameter of phase error. The combing efficiency's variance is related to not only the statistic parameter of phase errors, but also N. Once the statistic parameter of phase error is fixed, the greater the value of N, the smaller the variance is. So, in the engineering application, a large number of small power nodes could be used to reduce the phase error's effect. In addition, the influence of phase error on the combining efficiency is investigated by both theoretical analysis and the numerical simulation. The results show that when the array elements work at the same frequency, polarization and antenna type, the parameter of phase error would affect the combing result. The smaller the parameter of phase error, the larger the power of the effective point is, and the more concentrative the effective points' distribution is; the greater the parameter of phase error, the smaller the power of the effective point is, and the more dispersed the effective points' distribution is. It is also seen that even though the phase error occurs, the spatial power combining can still be realized with the time reversal technique. The determination of the phase control precision is the compromise between the requirements and the possibility. The results presented in this paper are useful for developing the microwave weapons with high power and electronic warfare.
We consider the synthesis of discrete finite-alphabet inputs for secure communications in multiple-input-single-output wiretap channels. We aim that the source with the synthesized transmissions can communicate with a legitimate receiver and degrade the performance of a potential eavesdropper. To this end, we formulate an optimization problem to minimize the Euclidean distance between the reference inputs and the synthesized inputs. We devise an iterative algorithm to tackle the non-convex design problem with constant-envelope constraints. Moreover, we extend the proposed methodology to deal with low peak-toaverage-power ratio transmissions. The numerical examples demonstrate that the proposed algorithms can achieve the requirement of secrecy communications efficiently. INDEX TERMS Transmission design, secrecy communication, constant-envelope, peak-to-average-power ratio (PAPR), MISO wiretap channel.
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