A Novel Joint Compressive Single Target Detection and Parameter Estimation in Radar without Signal Reconstruction
نویسندگان
چکیده
In this paper, a detector/estimator is proposed for compressed sensing radars, which does not need to reconstruct the radar signal, and which works directly from compressive measurements. More precisely, through direct processing of the measurements, and without the need for reconstructing the original radar signal, the system performs target detection, and then estimates range, Doppler frequency shift, and radar cross section in the presence of a Gaussian clutter. It can be seen that for large compression ratios, the detection performance and estimation quality is comparable to a common radar system while having a much lower data rate and with less computational load.
منابع مشابه
A Soft-Input Soft-Output Target Detection Algorithm for Passive Radar
Abstract: This paper proposes a novel scheme for multi-static passive radar processing, based on soft-input soft-output processing and Bayesian sparse estimation. In this scheme, each receiver estimates the probability of target presence based on its received signal and the prior information received from a central processor. The resulting posterior target probabilities are transmitted to the c...
متن کاملThrough-the-Wall Moving Target Detection and Localization using Sparse Regularization
In this paper, we consider moving target detection and localization inside enclosed structures for through-the-wall radar imaging and urban sensing applications. We exploit the fact that the through-the-wall scene is sparse in the Doppler domain, on account of the presence of a few moving targets in an otherwise stationary background. The sparsity property is used to achieve efficient joint ran...
متن کاملA Modified Regularized Adaptive Matching Pursuit Algorithm for Linear Frequency Modulated Signal Detection Based on Compressive Sensing
Compressive Sensing (CS) is a novel signal sampling theory under the condition that the signal is sparse or compressible. It has the ability of compressing a signal during the process of sampling. Reconstruction algorithm is one of the key parts in compressive sensing. We propose a novel iterative greedy algorithm for reconstructing sparse signals, called Modified Regularized Adaptive Matching ...
متن کاملSignal Detection and Parameter Estimation of Fence-type Space Surveillance Radar
Responding to the severe threat to the space activities from increasing LEO space debris, orbital object surveillance and cataloguing based on ground-based radar has aroused much attention from the world. However, the success of the space debris surveillance system strongly depends on the performance of signal detection and parameter estimation of the radar system. This paper presents a novel m...
متن کاملEfficiency of Target Location Scenarios in the Multi-Transmitter Multi-Receiver Passive Radar
Multi-transmitter multi-receiver passive radar, which locates target in the surveillance area by the reflected signals of the available opportunistic transmitter from the target, is of interest in many applications. In this paper, we investigate different signal processing scenarios in multi-transmitter multi-receiver passive radar. These scenarios include decentralized processing of reference ...
متن کامل