## 2021 |

Benavoli, Alessio; Balleri, Alessio; Farina, Alfonso Joint Waveform and Guidance Control Optimization by Statistical Linearisation for Target Rendezvous Conference IEEE Radar Conference 2021, May 8-14, Atlanta (USA), 2021. Abstract | Links | BibTeX | Tags: Cognitive radar, radar tracking @conference{Benavoli2021d, title = {Joint Waveform and Guidance Control Optimization by Statistical Linearisation for Target Rendezvous}, author = {Alessio Benavoli and Alessio Balleri and Alfonso Farina}, url = {http://alessiobenavoli.com/wp-content/uploads/2021/05/ieee_radarconf_21.pdf}, year = {2021}, date = {2021-05-18}, booktitle = { IEEE Radar Conference 2021, May 8-14, Atlanta (USA)}, abstract = {The algorithm proposed in this paper jointly selects the transmitted waveform and the control input so that a radar sensor on a moving platform can prosecute a target by minimising a predefined cost that accounts for the energy of the transmitted radar signal, the energy of the platform control input and the relative position error between the platform and the target. The cost is a function of the waveform design and control input. The algorithm extends the existing Joint Waveform Guidance and Control Optimisation (JWGCO) solution to non-linear equations to account for the dependency of the radar measurement accuracies on Signal to Noise Ratio (SNR) ratio and, as a consequence, the target position. The performance of the proposed solution based on statistical linearisation is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps.}, keywords = {Cognitive radar, radar tracking}, pubstate = {published}, tppubtype = {conference} } The algorithm proposed in this paper jointly selects the transmitted waveform and the control input so that a radar sensor on a moving platform can prosecute a target by minimising a predefined cost that accounts for the energy of the transmitted radar signal, the energy of the platform control input and the relative position error between the platform and the target. The cost is a function of the waveform design and control input. The algorithm extends the existing Joint Waveform Guidance and Control Optimisation (JWGCO) solution to non-linear equations to account for the dependency of the radar measurement accuracies on Signal to Noise Ratio (SNR) ratio and, as a consequence, the target position. The performance of the proposed solution based on statistical linearisation is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. |

## 2019 |

Benavoli, A; Balleri, A; Farina, A Joint Waveform and Guidance Control Optimization for Target Rendezvous Journal Article IEEE Transactions on Signal Processing, 67 (16), pp. 4357-4369, 2019, ISSN: 1053-587X. Abstract | Links | BibTeX | Tags: Cognitive radar, Kalman filter, linear quadratic Gaussian control @article{Benavoli2019d, title = {Joint Waveform and Guidance Control Optimization for Target Rendezvous}, author = {A Benavoli and A Balleri and A Farina}, url = {http://alessiobenavoli.com/wp-content/uploads/2019/08/Joint_waveform_and_guidance_control.pdf}, doi = {10.1109/TSP.2019.2929951}, issn = {1053-587X}, year = {2019}, date = {2019-08-01}, journal = {IEEE Transactions on Signal Processing}, volume = {67}, number = {16}, pages = {4357-4369}, abstract = {The algorithm developed in this paper jointly selects the optimal transmitted waveform and the control input so that a radar sensor on a moving platform with linear dynamics can reach a target by minimizing a predefined cost. The cost proposed in this paper accounts for the energy of the transmitted radar signal, the energy of the platform control input, and the relative position error between the platform and the target, which is a function of the waveform design and control input. Similarly to the linear quadratic Gaussian control problem, we demonstrate that the optimal solution satisfies the separation principle between filtering and optimization and, therefore, the optimum can be found analytically. The performance of the proposed solution is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. Results show the effectiveness of the proposed approach for optimal waveform design and optimal guidance control.}, keywords = {Cognitive radar, Kalman filter, linear quadratic Gaussian control}, pubstate = {published}, tppubtype = {article} } The algorithm developed in this paper jointly selects the optimal transmitted waveform and the control input so that a radar sensor on a moving platform with linear dynamics can reach a target by minimizing a predefined cost. The cost proposed in this paper accounts for the energy of the transmitted radar signal, the energy of the platform control input, and the relative position error between the platform and the target, which is a function of the waveform design and control input. Similarly to the linear quadratic Gaussian control problem, we demonstrate that the optimal solution satisfies the separation principle between filtering and optimization and, therefore, the optimum can be found analytically. The performance of the proposed solution is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. Results show the effectiveness of the proposed approach for optimal waveform design and optimal guidance control. |

# Publications

## 2021 |

Joint Waveform and Guidance Control Optimization by Statistical Linearisation for Target Rendezvous Conference IEEE Radar Conference 2021, May 8-14, Atlanta (USA), 2021. |

## 2019 |

Joint Waveform and Guidance Control Optimization for Target Rendezvous Journal Article IEEE Transactions on Signal Processing, 67 (16), pp. 4357-4369, 2019, ISSN: 1053-587X. |