SPARSE RECONSTRUCTION FOR NEAR-FIELD MIMO RADAR IMAGING USING FAST MULTIPOLE METHODS

Download
2022-1-27
Miran, Emre Alp
Multiple-input-multiple-output (MIMO) radar is an advanced radar technique, where spatially distributed transmitting and receiving sub-arrays operate sequentially or simultaneously. In this technique, each antenna may transmit either the same or different waveforms, and this leads to better spatial resolution when compared to conventional phased array radar. Therefore, MIMO radar has been extensively used in imaging applications in the last two decades. In all these applications, the imaged scene is typically sparse and objects of interest are located at the near-field of the antenna. More importantly, in most of these applications, the imaging system has to deal with the requirement of high quality real-time recovery from large-scale under-sampled measurement data. In this thesis, we aim to develop an efficient sparse solution method to large-scale near-field imaging problems. For this purpose, we first construct the imaging problem as a convex optimization problem and solve it using the augmented Lagrangian based reconstruction algorithms. Then, for large scale problems, we propose applying the fast multipole method (FMM) formulation in these algorithms for efficient computation of matrix-vector products. This approach avoids constructing and storing large-scale sensing matrices explicitly in memory and accelerates the reconstruction. We numerically test the effectiveness of the approach for several near-field imaging scenarios, ranging from point scatterers to extended targets (2-D/3-D). Results show that we can successfully apply FMM in the sparse reconstruction algorithms and it makes the reconstructions very efficient in terms of both computation time and memory usage.

Suggestions

Sparse Reconstruction for Near-Field MIMO Radar Imaging Using Fast Multipole Method
Miran, Emre A.; Öktem, Sevinç Figen; Koç, Seyit Sencer (2021-01-01)
Radar imaging using multiple input multiple output systems are becoming popular recently. These applications typically contain a sparse scene and the imaging system is challenged by the requirement of high quality real-time image reconstruction from under-sampled measurements via compressive sensing. In this paper, we deal with obtaining sparse solution to near- field radar imaging problems by developing efficient sparse reconstruction, which avoid storing and using large-scale sensing matrices. We demonstr...
Outlier robust filters and their multiple model extensions
Şahin Bozgan, İlknur; Özkan, Emre; Department of Electrical and Electronics Engineering (2019)
Kalman filter (KF), which is an algorithm that is utilized to estimate unknown variables based on noisy measurements, has been successfully employed in many applications such as navigation, control, signal processing and target tracking. It is the optimum Bayesian filter in terms of mean square error (MSE) for linear Gaussian state-space models (SSMs). However, in many real world applications, the performance of KF degrades due to the presence of outliers in noises. Motivated by this problem, several algori...
Spectral and statistical analyses of experimental radar clutter data
Kahyaoğlu, Nazlı Deniz; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2010)
The performance of radar detection and imaging systems strongly depends on the characteristics of radar clutter. In order to improve the radar signal processing algorithms, successful analysis and modeling of radar clutter are required. For a successful model of radar clutter, both the spectral and statistical characteristics of the clutter should be revealed. Within the scope of this study, an experimental radar data acquisition system is established to analyze radar clutter. The hardware and the data proc...
Design of Irregularly Shaped Patch Antennas by using the Multiport Network Model
Sener, Goker; Alatan, Lale; Kuzuoğlu, Mustafa (2008-07-11)
The multiport network model (MNM) is an analytical method that is used to analyze microstrip antennas. MNM is based on defining ports along the periphery of the patch and evaluating the impedance matrix corresponding to these ports by using the Greenpsilas function for the cavity under the patch. For regular rectangular, triangular and circular patches, analytical expressions for the Greenpsilas function are available. In the analysis of irregular patches, Greenpsilas functions cannot be calculated explicit...
Frequency Modulated Continuous Wave Radar for Range Detection
Kaya, Tevfik; Sahin, Enes Burak; Nesimoglu, Tayfun (2018-11-02)
In this paper, a Frequency Modulated Continuous Wave Radar is built using radio frequency techniques. Radar can measure the nearest object's range from 2 to 30 meters with 1-meter range resolution. The design process was carried out by using computer-aided design techniques, and mathematical tools. The hardware prototype was built and measurements were carried out confirming successful operation of the range detection radar.
Citation Formats
E. A. Miran, “SPARSE RECONSTRUCTION FOR NEAR-FIELD MIMO RADAR IMAGING USING FAST MULTIPOLE METHODS,” Ph.D. - Doctoral Program, Middle East Technical University, 2022.