Approximately Optimal Resource Management for Multi-Function Radar: Algorithmic Solutions Using a Generic Framework

Recent advances in Multi-Function Radar (MFR) systems led to an increase in their degrees of freedom. As a result, modern MFR systems are capable of adjusting many parameters during runtime. An automatic adaptation of the radar system to changing situations, like weather conditions, interference, or target maneuvers, is often mentioned in the...

A Constrained POMDP Formulation and Algorithmic Solution for Radar Resource Management in Multi-Target Tracking

The radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a...

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non...

Radar Resource Management for Multi-Target Tracking Using Model Predictive Control

The radar resource management problem in a multi-target tracking scenario is considered. Partially observable Markov decision processes (POMDPs) are used to describe each tracking task. Model predictive control is applied to solve the POMDPs in a non-myopic way. As a result, the computational complexity compared to stochastic optimization...

Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation

The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on...

Multi-Task Sensor Resource Balancing Using Lagrangian Relaxation and Policy Rollout

The sensor resource management problem in a multi-object tracking scenario is considered. In order to solve it, a dynamic budget balancing algorithm is proposed which models the different sensor tasks as partially observable Markov decision processes. Those are being solved by applying a combination of Lagrangian relaxation and policy rollout....

Using Golay Sequences to Improve the Range Performance of Hybrid Codes for MIMO Radar

In this paper, waveforms for MIMO phased array radar to enhance cross-range resolution are investigated. The problem of high sidelobes in range created by the use of Hybrid Codes with a single waveform and spatial coding is considered and a method to reduce these sidelobes by the use of Golay sequences as spatial codes is proposed. It is shown...