Applying multipartite entanglement purification protocol, we present a quantum key distribution p... more Applying multipartite entanglement purification protocol, we present a quantum key distribution protocol between two parties based on conference key agreement (or quantum secret sharing of classical secrets) as a generalization of quantum key distribution between two persons. We analyze the security of the protocol against an external eavesdropper and some dishonest members in two parties.
In this paper, we investigate properties of some multi-particle entangled states and, from the pr... more In this paper, we investigate properties of some multi-particle entangled states and, from the properties applying the secret sharing present a new type of quantum key distribution protocols as generalization of quantum key distribution between two persons. In the protocols each group can retrieve the secure key string, only if all members in each group should cooperate with one another. We also show that the protocols are secure against an external eavesdropper using the intercept/resend strategy.
In this paper, we present a protocol in which two or more parties can share multipartite entangle... more In this paper, we present a protocol in which two or more parties can share multipartite entanglement over noisy quantum channels. Applying this protocol to the quantum communication between several partners, we prove that the quantum communication for secret sharing is secure against all kinds of exterior eavesdropping.
We present a protocol for quantum cryptographic network consisting of a quantum network center an... more We present a protocol for quantum cryptographic network consisting of a quantum network center and many users, in which any pair of parties with members chosen from the whole users on request can secure a quantum key distribution by help of the center. The protocol is based on the quantum authentication scheme given by Barnum et al. [Proc. 43rd IEEE Symp. FOCS'02, p. 449 (2002)]. We show that exploiting the quantum authentication scheme the center can safely make two parties share nearly perfect entangled states used in the quantum key distribution. This implies that the quantum cryptographic network protocol is secure against all kinds of eavesdropping.
We present a protocol in which two or more parties can share multipartite entanglement over noisy... more We present a protocol in which two or more parties can share multipartite entanglement over noisy quantum channels. The protocol is based on the entanglement purification presented by Shor and Preskill [Phys. Rev. Lett. 85, 441 (2000)] and the quantum teleportation via an isotropic state. We show that a nearly perfect purification implies a nearly perfect sharing of multipartite entanglement between two parties so that the protocol can assure a faithful sharing of multipartite entanglement with Shor and Preskill's proof on the entanglement purification.
Sensor localization using channel energy measurements of distributed sensors has been studied in ... more Sensor localization using channel energy measurements of distributed sensors has been studied in various scenarios. However, it is usually assumed that the target does not move significantly during the time needed to collect and process the data from the sensors. We want to estimate the trajectory of a moving target using a network of distributed sensors that measure only the received signal strength (RSS), sampled and as a function of time, without knowledge of the target amplitude/source level. To reduce the communication load, sensors communicate a reduced data set to the fusion center (FC), generated through local processing. It consists of three characteristic parameters: i) the maximum measured amplitude, corresponding to the closest-point-of-approach (CPA); ii) the corresponding time index; and iii) the time it takes for the amplitude to diminish by 6 dB relative to the CPA. To generate the reduced data sets, each sensor calculates a local maximum likelihood (ML) estimate of its parameters. The accuracy of these local estimates can be reasonably described by their respective Fisher information matrices (FIMs). The FC combines the data transmitted by the sensors using a ML-like formulation based on the local FIMs. This results in a heavily non-linear least-squares problem, which we initialize via geometrical considerations. This approach has a very low communication load, performs comparably to a centralized estimator, and due to the modularized setup, any measurement model at the sensors can be considered.
We present a target tracking system for a specific sort of passive radar, that using a Digital Au... more We present a target tracking system for a specific sort of passive radar, that using a Digital Audio/Video Broadcast (DAB/DVB) network for illuminators of opportunity. The system can measure bi-static range and range-rate. Angular information is assumed here unavailable. The DAB/DVB network operates in a single frequency mode; this means the same data stream is broadcast from multiple senders in the same frequency band. This supplies multiple measurements of each target using just one receiver, but introduces an additional ambiguity, as the signals from each sender are indistinguishable. This leads to a significant data association problem: as well as the usual target/measurement uncertainty there is additional "list" of illuminators that must be contended with. Our intention is to provide tracks directly in the geographic space, as opposed to a two-step procedure of formation of tracks in (bi-static) range and range-rate space to fuse these onto a map. We offer two solutions: one employing joint probabilistic data association (JPDA) based on an Extended Kalman Filter (EKF), and the other a particle filter. For the former, we explain a "super-target" approach to bring what might otherwise be a three-dimensional assignment list down to the two dimensions the JPDAF needs. The latter approach would seem prohibitive in computation even with these; as such, we discuss the use of a PMHT-like measurement model that greatly reduces the numerical load.
Development of the novel homotopy, or particle-flow, nonlinear filters1-10 has recently been quit... more Development of the novel homotopy, or particle-flow, nonlinear filters1-10 has recently been quite rapid. There is actually a whole family of such methods, so we will refer to these collectively in this paper as "DH" filters, after their developers, the third and fourth authors of this manuscript. Unlike a particle filter, a DH filter does not resample; instead, the particles are moved in a smooth way, from a space that reflects prior (predicted) knowledge to one that is updated according to the measurements. Working versions of several DH filters now exist, and the purpose of this paper is to attempt to provide some perspective on them. We stress that this paper discusses the efforts of the first two authors to learn about and to explain in their own terms these these filters that others might benefit from that. The latter pair of authors - these are the developers of the DH filter family - have been instrumental in this effort. But it must be noted that they continue to develop their algorithms, and that this paper represents a snapshot of a rapidly changing landscape.
Source localization using channel energy measurements of distributed sensors has been well studie... more Source localization using channel energy measurements of distributed sensors has been well studied, but assumes the target not to move significantly during both the communication between the sensors and the calculation. We want to estimate the trajectory of a moving target, which passes through a sensor field. The sensors are simple in the sense that they can only measure the received signal strength (RSS), but no angular information; nor do they know the target source level. The target moves significantly between measurements, and communication between sensors only takes place at long intervals relative to the target motion. To reduce communication load, we suggest each sensor first processes its measurements locally and transmit only some aggregate value(s). Based on a free-space propagation model, we find each sensor should locally estimate three parameters to fully characterize its observations, namely the maximum measured amplitude, the corresponding time index and the speed with which the target signal fades, e.g, the time difference between the maximum and its 6 dB point. Based on two sensors, this allows us to reconstruct the target trajectory with only two possible mirror ambiguities, which could either be handled by a higher layer tracking algorithm as false alarms or resolved via a third sensor.
Applying multipartite entanglement purification protocol, we present a quantum key distribution p... more Applying multipartite entanglement purification protocol, we present a quantum key distribution protocol between two parties based on conference key agreement (or quantum secret sharing of classical secrets) as a generalization of quantum key distribution between two persons. We analyze the security of the protocol against an external eavesdropper and some dishonest members in two parties.
In this paper, we investigate properties of some multi-particle entangled states and, from the pr... more In this paper, we investigate properties of some multi-particle entangled states and, from the properties applying the secret sharing present a new type of quantum key distribution protocols as generalization of quantum key distribution between two persons. In the protocols each group can retrieve the secure key string, only if all members in each group should cooperate with one another. We also show that the protocols are secure against an external eavesdropper using the intercept/resend strategy.
In this paper, we present a protocol in which two or more parties can share multipartite entangle... more In this paper, we present a protocol in which two or more parties can share multipartite entanglement over noisy quantum channels. Applying this protocol to the quantum communication between several partners, we prove that the quantum communication for secret sharing is secure against all kinds of exterior eavesdropping.
We present a protocol for quantum cryptographic network consisting of a quantum network center an... more We present a protocol for quantum cryptographic network consisting of a quantum network center and many users, in which any pair of parties with members chosen from the whole users on request can secure a quantum key distribution by help of the center. The protocol is based on the quantum authentication scheme given by Barnum et al. [Proc. 43rd IEEE Symp. FOCS'02, p. 449 (2002)]. We show that exploiting the quantum authentication scheme the center can safely make two parties share nearly perfect entangled states used in the quantum key distribution. This implies that the quantum cryptographic network protocol is secure against all kinds of eavesdropping.
We present a protocol in which two or more parties can share multipartite entanglement over noisy... more We present a protocol in which two or more parties can share multipartite entanglement over noisy quantum channels. The protocol is based on the entanglement purification presented by Shor and Preskill [Phys. Rev. Lett. 85, 441 (2000)] and the quantum teleportation via an isotropic state. We show that a nearly perfect purification implies a nearly perfect sharing of multipartite entanglement between two parties so that the protocol can assure a faithful sharing of multipartite entanglement with Shor and Preskill's proof on the entanglement purification.
Sensor localization using channel energy measurements of distributed sensors has been studied in ... more Sensor localization using channel energy measurements of distributed sensors has been studied in various scenarios. However, it is usually assumed that the target does not move significantly during the time needed to collect and process the data from the sensors. We want to estimate the trajectory of a moving target using a network of distributed sensors that measure only the received signal strength (RSS), sampled and as a function of time, without knowledge of the target amplitude/source level. To reduce the communication load, sensors communicate a reduced data set to the fusion center (FC), generated through local processing. It consists of three characteristic parameters: i) the maximum measured amplitude, corresponding to the closest-point-of-approach (CPA); ii) the corresponding time index; and iii) the time it takes for the amplitude to diminish by 6 dB relative to the CPA. To generate the reduced data sets, each sensor calculates a local maximum likelihood (ML) estimate of its parameters. The accuracy of these local estimates can be reasonably described by their respective Fisher information matrices (FIMs). The FC combines the data transmitted by the sensors using a ML-like formulation based on the local FIMs. This results in a heavily non-linear least-squares problem, which we initialize via geometrical considerations. This approach has a very low communication load, performs comparably to a centralized estimator, and due to the modularized setup, any measurement model at the sensors can be considered.
We present a target tracking system for a specific sort of passive radar, that using a Digital Au... more We present a target tracking system for a specific sort of passive radar, that using a Digital Audio/Video Broadcast (DAB/DVB) network for illuminators of opportunity. The system can measure bi-static range and range-rate. Angular information is assumed here unavailable. The DAB/DVB network operates in a single frequency mode; this means the same data stream is broadcast from multiple senders in the same frequency band. This supplies multiple measurements of each target using just one receiver, but introduces an additional ambiguity, as the signals from each sender are indistinguishable. This leads to a significant data association problem: as well as the usual target/measurement uncertainty there is additional "list" of illuminators that must be contended with. Our intention is to provide tracks directly in the geographic space, as opposed to a two-step procedure of formation of tracks in (bi-static) range and range-rate space to fuse these onto a map. We offer two solutions: one employing joint probabilistic data association (JPDA) based on an Extended Kalman Filter (EKF), and the other a particle filter. For the former, we explain a "super-target" approach to bring what might otherwise be a three-dimensional assignment list down to the two dimensions the JPDAF needs. The latter approach would seem prohibitive in computation even with these; as such, we discuss the use of a PMHT-like measurement model that greatly reduces the numerical load.
Development of the novel homotopy, or particle-flow, nonlinear filters1-10 has recently been quit... more Development of the novel homotopy, or particle-flow, nonlinear filters1-10 has recently been quite rapid. There is actually a whole family of such methods, so we will refer to these collectively in this paper as "DH" filters, after their developers, the third and fourth authors of this manuscript. Unlike a particle filter, a DH filter does not resample; instead, the particles are moved in a smooth way, from a space that reflects prior (predicted) knowledge to one that is updated according to the measurements. Working versions of several DH filters now exist, and the purpose of this paper is to attempt to provide some perspective on them. We stress that this paper discusses the efforts of the first two authors to learn about and to explain in their own terms these these filters that others might benefit from that. The latter pair of authors - these are the developers of the DH filter family - have been instrumental in this effort. But it must be noted that they continue to develop their algorithms, and that this paper represents a snapshot of a rapidly changing landscape.
Source localization using channel energy measurements of distributed sensors has been well studie... more Source localization using channel energy measurements of distributed sensors has been well studied, but assumes the target not to move significantly during both the communication between the sensors and the calculation. We want to estimate the trajectory of a moving target, which passes through a sensor field. The sensors are simple in the sense that they can only measure the received signal strength (RSS), but no angular information; nor do they know the target source level. The target moves significantly between measurements, and communication between sensors only takes place at long intervals relative to the target motion. To reduce communication load, we suggest each sensor first processes its measurements locally and transmit only some aggregate value(s). Based on a free-space propagation model, we find each sensor should locally estimate three parameters to fully characterize its observations, namely the maximum measured amplitude, the corresponding time index and the speed with which the target signal fades, e.g, the time difference between the maximum and its 6 dB point. Based on two sensors, this allows us to reconstruct the target trajectory with only two possible mirror ambiguities, which could either be handled by a higher layer tracking algorithm as false alarms or resolved via a third sensor.
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