Target localization methods for frequency - only MIMO radar

Kalkan, Yılmaz
This dissertation is focused on developing the new target localization and the target velocity estimation methods for frequency-only multi-input, multi-output (MIMO) radar systems with widely separated antennas. If the frequency resolutions of the transmitted signals are enough, only the received frequencies and the Doppler shifts can be used to find the position of the target. In order to estimate the position and the velocity of the target, most multistatic radars or radar networks use multiple independent measurements from the target such as time-of-arrival (TOA), angle-of-arrival (AOA) and frequency-of-arrival (FOA). Although, frequency based systems have many advantages, frequency based target localization methods are very limited in literature because of the fact that highly non-linear equations are involved in solutions. In this thesis, alternative target localization and the target velocity estimation methods are proposed for frequency-only systems with low complexity. One of the proposed methods is able to estimate the target position and the target velocity based on the measurements of the Doppler frequencies. Moreover, the target movement direction can be estimated efficiently. This method is referred to as "Target Localization via Doppler Frequencies - TLDF" and it can be used for not only radar but also all frequency-based localization systems such as Sonar or Wireless Sensor Networks. Besides the TLDF method, two alternative target position estimation methods are proposed as well. These methods are based on the Doppler frequencies, but they requires the target velocity vector to be known. These methods are referred to as "Target Localization via Doppler Frequencies and Target Velocity - TLD&V methods" and can be divided two sub-methods. One of them is based on the derivatives of the Doppler Frequencies and hence it is called as "Derivated Doppler - TLD&V-DD method". The second method uses the Maximum Likelihood (ML) principle with grid search, hence it is referred to as "Sub-ML, TLD&V-subML method". The more realistic signal model for ground based, widely separated MIMO radar is formed as including Swerling target fluctuations and the Doppler frequencies. The Cramer-Rao Bounds (CRB) are derived for the target position and the target velocity estimations for this signal model. After the received signal is constructed, the Doppler frequencies are estimated by using the DFT based periodogram spectral estimator. Then, the estimated Doppler frequencies are collected in a fusion center to localize the target. Finally, the multiple targets localization problem is investigated for frequency-only MIMO radar and a new data association method is proposed. By using the TLDF method, the validity of the method is simulated not only for the targets which are moving linearly but also for the maneuvering targets. The proposed methods can localize the target and estimate the velocity of the target with less error according to the traditional isodoppler based method. Moreover, these methods are superior than the traditional method with respect to the computational complexity. By using the simulations with MATLAB, the superiorities of the proposed methods to the traditional method are shown.


Target Localization and Velocity Estimation Methods for Frequency-Only MIMO Radars
Kalkan, Yilmaz; Baykal, Buyurman (2011-05-27)
Target localization and the velocity estimation methods are proposed for frequency-only MIMO Radar with widely separated stations. For the target localization, time of arrival (TOA), angle of arrival (AOA) and frequency of arrival (FOA) informations can be used in cooperation. When the time resolution of the transmitted signals is not enough or good,i.e.; unmodulated CW radar, we can not rely on the TOA information to localize the target. On the other hand, if the frequency resolution of the transmitted sig...
Multi-target tracking using passive doppler measurements
Guldogan, Mehmet B.; Orguner, Umut; Gustafsson, Fredrik (2013-04-26)
In this paper, we analyze the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple non-cooperative targets using Doppler-only measurements in a passive sensor network. Clutter, missed detections and multi-static Doppler variances are incorporated into a realistic multi-target scenario. Simulation results show that the GM-PHD filter successfully tracks multiple targets using only Doppler shift measurements in a passive multi-static scenario.
Slow moving target detection for airborne radar systems by dynamic programming on SAR images
Gurer, Gorkem; Koc, Sencer; Candan, Çağatay; Orguner, Umut (2019-04-01)
A dynamic programming based approach is proposed to detect slow moving, low reflectivity targets for airborne radar systems. The suggested method utilizes the reflectivity amplitudes of the SAR image, possibly containing multiple slow moving targets, and poses the target detection problem as a maximum likelihood sequence detection problem. Dynamic programming is applied to capture the target related features such as along track smeared target signatures in the SAR image to this aim. Typical clutter and targ...
Target tracking and sensor placement for doppler–only measurements
Ayazgök, Süleyman; Orguner, Umut; Department of Electrical and Electronics Engineering (2015)
This thesis investigates the problems of target tracking and optimal sensor placement with Doppler-only measurements. First, a single point track initialization algorithm proposed in the literature is investigated for Doppler-only tracking. The initialization algorithm is based on separable least squares method and involves a grid-based optimization. Second, particle filters are considered for Doppler-only tracking and they are compared to an extended Kalman filter (EKF). It is shown that a classical bootst...
Multi-dimensional hough transform based on unscented transform as a method of track-before-detect /
Şahin, Gözde; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2014)
Track-Before-Detect (TBD) is the problem where target state estimation and detection occur simultaneously, and is a suitable method for the detection of low-SNR targets in unthresholded sensor data. In this thesis, a new Multi-Dimensional Hough Transform (MHT) technique based on Unscented Transform is proposed for the detection of dim targets in radar data. MHT is a TBD method that fuses Hough Transform results obtained on (x-t), (y-t) and (x-y) domains in order to detect a constant velocity target. The pro...
Citation Formats
Y. Kalkan, “Target localization methods for frequency - only MIMO radar,” Ph.D. - Doctoral Program, Middle East Technical University, 2012.