Peter Willett - Academia.edu (original) (raw)
Papers by Peter Willett
Proceedings of SPIE, May 2, 2017
Proceedings of SPIE, May 17, 2016
IEEE Transactions on Signal Processing, May 1, 2016
IEEE Aerospace and Electronic Systems Magazine, 2017
IEEE Aerospace and Electronic Systems Magazine, 2018
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](IEEE Signal Processing Magazine, 2018
IEEE Aerospace and Electronic Systems Magazine, 2019
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
IEEE Transactions on Aerospace and Electronic Systems, Oct 1, 2015
International Conference on Information Fusion, Jul 5, 2016
IEEE Transactions on Signal Processing, Jul 1, 2017
MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM), Nov 29, 2021
A new algorithm for 3D localization in multiplat-form radar networks, comprising one transmitter ... more A new algorithm for 3D localization in multiplat-form radar networks, comprising one transmitter and multiple receivers, is proposed. To take advantage of the monostatic sensor radiation pattern features, angular constraints are imposed in the target localization process, restricting the azimuth-elevation location of any illuminated target. This is formulated as a non-convex constrained Least Squares (LS) optimization problem globally solved in a quasi-closed-form leveraging Karush-Kuhn-Tucker (KKT) conditions. The performance of the new algorithm is assessed in terms of the Root Mean Square Error (RMSE) and compared with the benchmark Root Cramer Rao Lower Bound (RCRLB) and some competitors from literature. The results corroborate the effectiveness of the new strategy which is capable of ensuring a lower RMSE than the counterpart methodologies especially in the low Signal to Noise Ratio (SNR) regime.
Recent research activities have investigated the feasibility of detecting ship targets from Globa... more Recent research activities have investigated the feasibility of detecting ship targets from Global Navigation Satellite System-Reflectometry (GNSS-R) receivers. It was concluded by both experimental and theoretical analyses that ship detection is infeasible from spaceborne receivers working in a conventional configuration. On the other hand, it was demonstrated that performance might be boosted by receiving the right-hand circular polarization (RHCP) channel in a backscattering configuration. In this paper, we assess the detectability of ship targets in GNSS-R delay-Doppler maps by means of a reliable stochastic GNSS-R simulation tool capable of accounting for the presence of the target. The results mainly confirm the previous theoretical analyses and demonstrate the feasibility of the ship detection problem using low-altitudes RHCP-backscattering GNSS-R.
Proceedings of SPIE, Jun 13, 2014
ABSTRACT We discuss a procedure to estimate the state of thrusting/ballistic endoatmospheric proj... more ABSTRACT We discuss a procedure to estimate the state of thrusting/ballistic endoatmospheric projectiles for the purpose of impact point prediction (IPP). The short observation time and the estimation ambiguity between drag and thrust in the dynamic model motivate the development of a multiple interacting multiple model (MIMM) estimator with various drag coefficient initializations. In each IMM estimator used, as the mode-matched state estimators for its thrusting mode and ballistics mode are of unequal dimension, an unbiased mixing is required. We explore the MIMM estimator with unbiased mixing (UM) using extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle filter (PF). For 30 real trajectories, the IPP based on the MIMM-UM estimation approach is carried out with various sets of tuning parameters selected. The MIMM-UM-EKF, MIMM-UM-UKF and MIMM-UM-PF are compared based on the resulting IPP performance, estimator consistency and computational complexity.
If two radar sensors observe the same target their measurements can be combined to produce a fuse... more If two radar sensors observe the same target their measurements can be combined to produce a fused target-state estimate that is of higher quality than that from one radar alone. If there are multiple targets whose information is shared, a necessary first step to fusion is to “assign” each measurement from the first sensor to that at the other in such a way that both refer to the same underlying object, a task generally accomplished by minimizing a global cost involving distance. An assignment error occurs when the measurement originated by target i at the first radar is wrongly associated to a measurement originated by target jjj (not i) at the second radar. Naturally, when such an error occurs the result is fusion of information describing disparate objects, resulting in degraded estimation performance and poor self-assessment in terms of posterior uncertainty. Here we address the issue, and derive approximate assignment error probability. Remarkably, performance depends only upon the parameters combined to a single scalar constant.
International Conference on Information Fusion, Jul 6, 2015
Driven by real-world issues in maritime surveillance, we consider the problem of estimating the t... more Driven by real-world issues in maritime surveillance, we consider the problem of estimating the target state from a sequence of observations that can be imprecisely time-stamped. That is, the time between two consecutive observations can be affected by an unknown error or delay. We propose an adaptive filtering strategy able to sequentially detect the time delays and correctly estimate the target state. Two decision statistics for the presence of delay are derived, the first is non-parametric while the second is based on the Generalized Likelihood Ratio Test (GLRT). When a delayed measurement is detected, the Maximum Likelihood (ML) estimate of the delay can be used to correct the timestamps of the target observation used in the filter. The validation of the proposed method is carried out using Monte Carlo computer simulations and analyzing real-world data collected by a global network of Automatic Identification System (AIS) receivers.
Proceedings of SPIE, May 2, 2017
Proceedings of SPIE, May 17, 2016
IEEE Transactions on Signal Processing, May 1, 2016
IEEE Aerospace and Electronic Systems Magazine, 2017
IEEE Aerospace and Electronic Systems Magazine, 2018
IEEE Signal Processing Magazine, 2018
IEEE Aerospace and Electronic Systems Magazine, 2019
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
IEEE Transactions on Aerospace and Electronic Systems, Oct 1, 2015
International Conference on Information Fusion, Jul 5, 2016
IEEE Transactions on Signal Processing, Jul 1, 2017
MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM), Nov 29, 2021
A new algorithm for 3D localization in multiplat-form radar networks, comprising one transmitter ... more A new algorithm for 3D localization in multiplat-form radar networks, comprising one transmitter and multiple receivers, is proposed. To take advantage of the monostatic sensor radiation pattern features, angular constraints are imposed in the target localization process, restricting the azimuth-elevation location of any illuminated target. This is formulated as a non-convex constrained Least Squares (LS) optimization problem globally solved in a quasi-closed-form leveraging Karush-Kuhn-Tucker (KKT) conditions. The performance of the new algorithm is assessed in terms of the Root Mean Square Error (RMSE) and compared with the benchmark Root Cramer Rao Lower Bound (RCRLB) and some competitors from literature. The results corroborate the effectiveness of the new strategy which is capable of ensuring a lower RMSE than the counterpart methodologies especially in the low Signal to Noise Ratio (SNR) regime.
Recent research activities have investigated the feasibility of detecting ship targets from Globa... more Recent research activities have investigated the feasibility of detecting ship targets from Global Navigation Satellite System-Reflectometry (GNSS-R) receivers. It was concluded by both experimental and theoretical analyses that ship detection is infeasible from spaceborne receivers working in a conventional configuration. On the other hand, it was demonstrated that performance might be boosted by receiving the right-hand circular polarization (RHCP) channel in a backscattering configuration. In this paper, we assess the detectability of ship targets in GNSS-R delay-Doppler maps by means of a reliable stochastic GNSS-R simulation tool capable of accounting for the presence of the target. The results mainly confirm the previous theoretical analyses and demonstrate the feasibility of the ship detection problem using low-altitudes RHCP-backscattering GNSS-R.
Proceedings of SPIE, Jun 13, 2014
ABSTRACT We discuss a procedure to estimate the state of thrusting/ballistic endoatmospheric proj... more ABSTRACT We discuss a procedure to estimate the state of thrusting/ballistic endoatmospheric projectiles for the purpose of impact point prediction (IPP). The short observation time and the estimation ambiguity between drag and thrust in the dynamic model motivate the development of a multiple interacting multiple model (MIMM) estimator with various drag coefficient initializations. In each IMM estimator used, as the mode-matched state estimators for its thrusting mode and ballistics mode are of unequal dimension, an unbiased mixing is required. We explore the MIMM estimator with unbiased mixing (UM) using extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle filter (PF). For 30 real trajectories, the IPP based on the MIMM-UM estimation approach is carried out with various sets of tuning parameters selected. The MIMM-UM-EKF, MIMM-UM-UKF and MIMM-UM-PF are compared based on the resulting IPP performance, estimator consistency and computational complexity.
If two radar sensors observe the same target their measurements can be combined to produce a fuse... more If two radar sensors observe the same target their measurements can be combined to produce a fused target-state estimate that is of higher quality than that from one radar alone. If there are multiple targets whose information is shared, a necessary first step to fusion is to “assign” each measurement from the first sensor to that at the other in such a way that both refer to the same underlying object, a task generally accomplished by minimizing a global cost involving distance. An assignment error occurs when the measurement originated by target i at the first radar is wrongly associated to a measurement originated by target jjj (not i) at the second radar. Naturally, when such an error occurs the result is fusion of information describing disparate objects, resulting in degraded estimation performance and poor self-assessment in terms of posterior uncertainty. Here we address the issue, and derive approximate assignment error probability. Remarkably, performance depends only upon the parameters combined to a single scalar constant.
International Conference on Information Fusion, Jul 6, 2015
Driven by real-world issues in maritime surveillance, we consider the problem of estimating the t... more Driven by real-world issues in maritime surveillance, we consider the problem of estimating the target state from a sequence of observations that can be imprecisely time-stamped. That is, the time between two consecutive observations can be affected by an unknown error or delay. We propose an adaptive filtering strategy able to sequentially detect the time delays and correctly estimate the target state. Two decision statistics for the presence of delay are derived, the first is non-parametric while the second is based on the Generalized Likelihood Ratio Test (GLRT). When a delayed measurement is detected, the Maximum Likelihood (ML) estimate of the delay can be used to correct the timestamps of the target observation used in the filter. The validation of the proposed method is carried out using Monte Carlo computer simulations and analyzing real-world data collected by a global network of Automatic Identification System (AIS) receivers.