9 accepted papers
This paper proposes a cognitive beamforming method for target tracking using multiple-input multiple-output (MIMO) radar. This method minimizes a Bayesian performance criterion on direction-of-arrival (DOA) estimation error with respect to the transmit signal auto-correlation matrix. Traditionally,…
One-bit quantization has gained significant attention in communications and signal processing due to its potential for reducing energy consumption and system costs. However, parameter estimation methods that account for the quantization model tend to be complex and computationally intensive. Consequ…
In many applications of estimation theory, the true data model is not perfectly known, leading to mismatch between the assumed model used for parameter estimation and the actual model. The non-Bayesian misspecified Cramér-Rao bound (MCRB) allows considering the effect of model misspecification on th…
Automotive radar is the main sensor enabling autonomous driving and active safety features. It is required to provide high-resolution information on the vehicle’s surroundings, accurately localize surrounding objects, and estimate their velocity in two dimensions. Conventional automotive radars oper…
In many applications of estimation theory, the true data model is unknown, and a set of parameterized models are used to approximate it. This problem is encountered in learning systems, where the assumed model parameters are estimated using training data. One of the challenges in these problems is c…
This paper deals with non-Bayesian parameter estimation under the mean-squared-error (MSE), which is a topic of great interest in various engineering fields. Although the unbiasedness condition is commonly used in non-Bayesian MSE estimation, in many cases biased estimation may result in better perf…
How accurately can one estimate a deterministic parameter subject to other unknown deterministic model parameters? The most popular answer to this question is given by the Cramer-Rao bound (CRB). The main assumption behind the derivation of the CRB is local unbiased estimation of all model parameter…
Parameter estimation using quantized observations is of importance in many practical applications. Under a symmetric 1-bit setup, consisting of a zero-threshold hard-limiter, it is well known that the large sample performance loss for low signal-to-noise ratios (SNRs) is moderate (2/Π or -1.96dB). T…
Tracking problems are usually investigated using the Bayesian approach. Many practical tracking problems involve some unknown deterministic nuisance parameters such as the system parameters or noise statistical parameters. This paper addresses the problem of state estimation in linear discrete-time…