Sensor cooperative scheduling method for low-altitude maneuvering target tracking in complex environment

Purpose Continuous and stable tracking of the low-altitude maneuvering targets is usually difficult due to terrain occlusion and Doppler blind zone (DBZ). This paper aims to present a non-myopic scheduling method of multiple radar sensors for tracking the low-altitude maneuvering targets. In this scheduling problem, the best sensors are systematically selected to observe targets for getting the best tracking accuracy under maintaining the low intercepted probability of a multi-sensor system. Design/methodology/approach First, the sensor scheduling process is formulated within the partially observable Markov decision process framework. Second, the interacting multiple model algorithm and the cubature Kalman filter algorithm are combined to estimate the target state, and the DBZ information is applied to estimate the target state when the measurement information is missing. Then, an approximate method based on a cubature sampling strategy is put forward to calculate the future expected objective of the multi-step scheduling process. Furthermore, an improved quantum particle swarm optimization (QPSO) algorithm is presented to solve the sensor scheduling action quickly. Optimization problem, an improved QPSO algorithm is presented to solve the sensor scheduling action quickly. Findings Compared with the traditional scheduling methods, the proposed method can maintain higher target tracking accuracy with a low intercepted probability. And the proposed target state estimation method in DBZ has better tracking performance. Originality/value In this paper, DBZ, sensor intercepted probability and complex terrain environment are considered in sensor scheduling, which has good practical application in a complex environment.

Making Reflective Equlibrium Precise: A Formal Model

Reflective equilibrium (RE) is often regarded as a powerful method in ethics, logic, and even philosophy in general. Despite this popularity, characterizations of the method have been fairly vague and unspecific so far. It thus may be doubted whether RE is more than a jumble of appealing but ultimately sketchy ideas that cannot be spelled out consistently. In this paper, we dispel such doubts by devising a formal model of RE. The model contains as components the agent’s commitments and a theory that tries to systematize the commitments. It yields a precise picture of how the commitments and the theory are adjusted to each other. The model differentiates between equilibrium as a target state and the dynamic equilibration process. First solutions to the model, obtained by computer simulation, show that the method allows for consistent specification and that the model’s implications are plausible in view of expectations on RE. In particular, the mutual adjustment of commitments and theory can improve one’s commitments, as proponents of RE have suggested. We argue that our model is fruitful not only because it points to issues that need to be dealt with for a better understanding of RE, but also because it provides the means to address these issues.

Receiver selection for multi-target tracking in multi-static Doppler radar systems

This paper presents a novel receiver selection method for multi-target tracking in multi-static Doppler radar systems. The assumption is that in the surveillance volume of interest, a single transmitter with a known frequency is active and several spatially distributed radar receivers collect and report Doppler-only measurements. The Doppler measurements are not only affected by the additive noise but also contaminated by false and missed detections. In this paper, multi-target tracking is obtained by modeling the multi-target state as a labeled multi-Bernoulli random finite set and receiver selection is implemented during tracking. Receiver selection is solved under the partially observed Markov decision framework, and the variance of the cardinality estimate is used as the selection criterion. To increase the diversity of the selected sensors and overcome the low observability of the Doppler measurement, the receivers selected at previous time steps are taken into account by adding a window. Simulation studies demonstrate the tracking performance of the proposed method with different window lengths. The results show that the observability of the target state is a crucial factor in determining the performance of receiver selection. The proposed method with a suitable window length can effectively improve the tracking accuracy.

Nonlocal implementation of multi-qubit controlled unitary quantum gates with quantum channel

Quantum computers are very efficient in terms of speed and security. Decoherence and architectural complexity restrict the control of sensitive quantum information as the number of qubits in a quantum computer increases. Therefore, it is more convenient to make a device with multiple quantum processors with small number of qubits instead of making a device with a large number of qubits quantum processors. The implementation of controlled unitary gates is a problem in such nonlocal systems. The methods in the literature for this problem use entangled qubit pairs, classical communication channels and classical bits. The existing methods perform some unitary operations on the target state for reconstruction after sending information through classical communication channels and applying quantum measurements on control states. In this study, a generalized method for nonlocal implementation of multi-qubit controlled unitary quantum gates with quantum channel is proposed. The proposed method can implement any controlled gate on the control and target qubits that are far from each other in terms of location. The method does not require classical channels and classical bits, any extra unitary operation for reconstruction. The proposed method is both more secure and uses less resources for operations than the other hybrid methods in the literature. Comparisons with existing studies are given in terms of required entangled qubit pairs, classical channels and bits, extra unitary operations for reconstruction the target state, and the advantages of the proposed method are revealed.

An EM Algorithm for Target Tracking with an Unknown Correlation Coefficient of Measurement Noise

In this paper, an expectation maximization based sequential modified unbiased converted measurement Kalman filter is proposed for target tracking with an unknown correlation coefficient of measurement noise between the range and the range rate. Firstly, a pseudo measurement is constructed by multiplying the range and the range rate to reduce the strong nonlinearity between the measurement and the target state. The mean and covariance of converted errors are subsequentlsubsequently derived by modified unbiased converted measurement to weaken the error caused by the linearization of the measurement equation, which is effectively to improve the dynamic accuracy of target tracking. Then, the converted errors of the position and the pseudo measurement are decorrelated by the Cholesky factorization and thus to obtain the posterior probability distribution of the state by using the sequential filtering in the Bayesian framework. Finally, the expectation maximization is introduced in the updating procedure of the pseudo measurement to jointly estimate the target state and the correlation coefficient. The target tracking scenario with an unknown correlation coefficient is built to demonstrate the validness and feasibility of the proposed algorithm. Simultaneously, the results of the normalized error squared validate the consistency of the modified unbiased converted measurement.

EUROPEAN UNION (EU) SANCTIONS ON ZIMBABWE (2002-2013): TESTING HYPOTHESES OF INFLUENCE IN POLITICAL SCIENCE

The focus of this article was to test the hypotheses (factors) of influence that enabled the EU and its partners to exert influence in Zimbabwe between 2002 and 2013. Four hypotheses volume of actions, severity of actions, commitment and the timing of actions have been tested. The article has also tested four hypotheses of non-influence (detracting factors) prestige, desirability of violations, internal power struggles and aid-dependence exhibited by the Mugabe regime during this period. The article concludes that it was due to the overwhelming weight of the foreign policy actions over the internal situation of Zimbabwe that finally pushed Mugabe to bowed down. The great lesson learned from the Zimbabwe experience is that the influencing state must evaluate the detracting factors in the target state well in order to select and maximise on the best influencing actions.