126 research outputs found
Adaptive Radar Detection of Dim Moving Targets in Presence of Range Migration
This paper addresses adaptive radar detection of dim moving targets. To
circumvent range migration, the detection problem is formulated as a multiple
hypothesis test and solved applying model order selection rules which allow to
estimate the "position" of the target within the CPI and eventually detect it.
The performance analysis proves the effectiveness of the proposed approach also
in comparison to existing alternatives.Comment: 5 pages, 2 figures, submitted to IEEE Signal Processing Letter
Bayesian sparse representation in colored noise: prewhitening vs joint estimation
In this paper, we consider the problem of designing sparse signal representation (SSR) amid colored noise. Two processing architectures are examined under a Bayesian framework: i) a two-stage processing with a prewhitening operation followed by SSR assuming a perfect white noise ii) a joint approach estimating at the same time the sparse signal and the colored noise. Both approaches are compared; performance is numerically studied in case of conventional radar scenarios. Results show that the joint algorithm outperforms to some extent the prewhitened approach but at the expense of a higher complexity
ΠΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π·Π°ΡΡΠΌΠ»Π΅Π½Π½ΡΡ ΡΠΈΠ³Π½Π°Π»ΠΎΠ² Ρ ΡΠ½ΠΈΠΌΠΎΠ΄Π°Π»ΡΠ½ΡΠΌ ΡΠΏΠ΅ΠΊΡΡΠΎΠΌ
ΠΠΎΠ»Π½ΡΠΉ ΡΠ΅ΠΊΡΡ Π΄ΠΎΡΡΡΠΏΠ΅Π½ Π½Π° ΡΠ°ΠΉΡΠ΅ ΠΈΠ·Π΄Π°Π½ΠΈΡ ΠΏΠΎ ΠΏΠΎΠ΄ΠΏΠΈΡΠΊΠ΅: http://radio.kpi.ua/article/view/S0021347019010059ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅ΡΠΎΠ΄ Π²ΠΎΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΡ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠΎΠ² Π΄ΠΈΡΠΊΡΠ΅ΡΠ½ΠΎΠΉ Π°Π²ΡΠΎΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ½ΠΊΡΠΈΠΈ ΡΠ»ΡΡΠ°ΠΉΠ½ΡΡ
ΡΠΈΠ³Π½Π°Π»ΠΎΠ² Ρ ΡΠ½ΠΈΠΌΠΎΠ΄Π°Π»ΡΠ½ΠΎΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΡΡ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ Π΄Π»Ρ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ. ΠΠ΅ΡΠΎΠ΄ Π±Π°Π·ΠΈΡΡΠ΅ΡΡΡ Π½Π° Π½Π°Ρ
ΠΎΠΆΠ΄Π΅Π½ΠΈΠΈ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠΈΡΠΈΠ½Ρ ΞFT ΠΈ Π²Π΅ΡΠΎΠ²ΠΎΠ³ΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Ξ± Π² Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π΅ [0; 1] ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Ρ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠ΅Π³ΠΎ Π΄ΠΎΠ»ΠΈ Π³Π°ΡΡΡΠΎΠ²ΡΠΊΠΎΠΉ ΠΈ ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΠ½ΠΎΠΉ ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΡ
Π² ΠΎΠ³ΠΈΠ±Π°ΡΡΠ΅ΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΠΉ ΠΌΠ΅ΡΠΎΠ΄ Π΄Π°Π΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΡΠΌΠ΅Π½ΡΡΠΈΡΡ Π² 1,5β4 ΡΠ°Π·Π° Π½Π΅Π²ΡΠ·ΠΊΡ ΠΌΠ΅ΠΆΠ΄Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»ΡΠ½ΡΠΌ ΠΈ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π΅ΠΌΡΠΌ ΡΠΏΠ΅ΠΊΡΡΠ°ΠΌΠΈ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΠΌΠΈ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π°ΠΌΠΈ ΠΊ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΌΡ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΌΡ Π°Π½Π°Π»ΠΈΠ·Ρ. Π£Π²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎΡΡΠΈ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π½ΠΈΡ Π΄Π°Π΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΡΠΎΠΊΡΠ°ΡΠΈΡΡ Π² 2,3β4 ΡΠ°Π·Π° Π΄Π»ΠΈΠ½Ρ M Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΠΎΠΉ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π²ΡΠ±ΠΎΡΠΊΠΈ ΠΏΡΠΈ ΡΠΎΡ
ΡΠ°Π½Π΅Π½ΠΈΠΈ Π΄ΠΎΡΡΠΈΠ³Π°Π΅ΠΌΠΎΠΉ Π΄ΡΡΠ³ΠΈΠΌΠΈ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΠΌΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ ΡΠΎΡΠ½ΠΎΡΡΠΈ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°. ΠΡΠΈΠ³ΡΡΡΠΈ Π΄ΠΎΡΡΠΈΠ³Π°ΡΡΡΡ Π·Π° ΡΡΠ΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π°ΠΏΡΠΈΠΎΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΎ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΡΡ
ΡΠ²ΠΎΠΉΡΡΠ²Π°Ρ
Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°
BIO-INSPIRED SONAR IN COMPLEX ENVIRONMENTS: ATTENTIVE TRACKING AND VIEW RECOGNITION
Bats are known for their unique ability to sense the world through echolocation. This allows them to perceive the world in a way that few animals do, but not without some difficulties. This dissertation explores two such tasks using a bio-inspired sonar system: tracking a target object in cluttered environments, and echo view recognition. The use of echolocation for navigating in dense, cluttered environments can be a challenge due to the need for rapid sampling of nearby objects in the face of delayed echoes from distant objects. If long-delay echoes from a distant object are received after the next pulse is sent out, these βaliasedβ echoes appear as close-range phantom objects. This dissertation presents three reactive strategies for a high pulse-rate sonar system to combat aliased echoes: (1) changing the interpulse interval to move the aliased echoes away in time from the tracked target, (2) changing positions to create a geometry without aliasing, and (3) a phase-based, transmission beam-shaping strategy to illuminate the target and not the aliasing object. While this task relates to immediate sensing needs and lower level motor loops, view recognition is involved in higher level navigation and planning. Neurons in the mammalian brain (specifically in the hippocampus formation) named βplace cellsβ are thought to reflect this recognition of place and are involved in implementing a spatial map that can be used for path planning and memory recall. We propose hypothetical βecho view cellsβ that could contribute (along with odometry) to the creation of place cell representations actually observed in bats. We strive to recognize views over extended regions that are many body lengths in size, reducing the number of places to be remembered for a map. We have successfully demonstrated some of this spatial invariance by training feed-forward neural networks (traditional neural networks and spiking neural networks) to recognize 66 distinct places in a laboratory environment over a limited range of translations and rotations. We further show how the echo view cells respond in between known places and how the population of cell outputs can be combined over time for continuity
Doppler Radar Techniques for Distinct Respiratory Pattern Recognition and Subject Identification.
Ph.D. Thesis. University of HawaiΚ»i at MΔnoa 2017
DragonflEYE: a passive approach to aerial collision sensing
"This dissertation describes the design, development and test of a passive wide-field optical aircraft collision sensing instrument titled 'DragonflEYE'. Such a ""sense-and-avoid"" instrument is desired for autonomous unmanned aerial systems operating in civilian airspace. The instrument was configured as a network of smart camera nodes and implemented using commercial, off-the-shelf components. An end-to-end imaging train model was developed and important figures of merit were derived. Transfer functions arising from intermediate mediums were discussed and their impact assessed. Multiple prototypes were developed. The expected performance of the instrument was iteratively evaluated on the prototypes, beginning with modeling activities followed by laboratory tests, ground tests and flight tests. A prototype was mounted on a Bell 205 helicopter for flight tests, with a Bell 206 helicopter acting as the target. Raw imagery was recorded alongside ancillary aircraft data, and stored for the offline assessment of performance. The ""range at first detection"" (R0), is presented as a robust measure of sensor performance, based on a suitably defined signal-to-noise ratio. The analysis treats target radiance fluctuations, ground clutter, atmospheric effects, platform motion and random noise elements. Under the measurement conditions, R0 exceeded flight crew acquisition ranges. Secondary figures of merit are also discussed, including time to impact, target size and growth, and the impact of resolution on detection range. The hardware was structured to facilitate a real-time hierarchical image-processing pipeline, with selected image processing techniques introduced. In particular, the height of an observed event above the horizon compensates for angular motion of the helicopter platform.
OFDM passive radar employing compressive processing in MIMO conο¬gurations
A key advantage of passive radar is that it provides a means of performing position detection and tracking without the need for transmission of energy pulses. In this respect, passive radar systems utilising (receiving) orthogonal frequency division multiplexing (OFDM) communications signals from transmitters using OFDM standards such as long term evolution (LTE), WiMax or WiFi, are considered. Receiving a stronger reference signal for the matched ο¬ltering, detecting a lower target signature is one of the challenges in the passive radar. Impinging at the receiver, the OFDM waveforms supply two-dimensional virtual uniform rectangul ararray with the ο¬rst and second dimensions refer to time delays and Doppler frequencies respectively. A subspace method, multiple signals classiο¬cation (MUSIC) algorithm, demonstrated the signal extraction using multiple time samples. Apply normal measurements, this problem requires high computational resources regarding the number of OFDM subcarriers. For sub-Nyquist sampling, compressive sensing (CS) becomes attractive. A single snap shot measurement can be applied with Basis Pursuit (BP), whereas l1-singular value decomposition (l1-SVD) is applied for the multiple snapshots. Employing multiple transmitters, the diversity in the detection process can be achieved. While a passive means of attaining three-dimensional large-set measurements is provided by co-located receivers, there is a signiο¬cant computational burden in terms of the on-line analysis of such data sets. In this thesis, the passive radar problem is presented as a mathematically sparse problem and interesting solutions, BP and l1-SVD as well as Bayesian compressive sensing, fast-Besselk, are considered. To increase the possibility of target signal detection, beamforming in the compressive domain is also introduced with the application of conve xoptimization and subspace orthogonality. An interference study is also another problem when reconstructing the target signal. The networks of passive radars are employed using stochastic geometry in order to understand the characteristics of interference, and the effect of signal to interference plus noise ratio (SINR). The results demonstrate the outstanding performance of l1-SVD over MUSIC when employing multiple snapshots. The single snapshot problem along with fast-BesselK multiple-input multiple-output conο¬guration can be solved using fast-BesselK and this allows the compressive beamforming for detection capability
Three Dimensional Bistatic Tomography Using HDTV
The thesis begins with a review of the principles of diffraction and reflection tomography; starting with the analytic solution to the inhomogeneous Helmholtz equation, after linearization by the Born approximation (the weak scatterer solution), and arriving at the Filtered Back Projection (Propagation) method of reconstruction. This is followed by a heuristic derivation more directly couched in the radar imaging context, without the rigor of the general inverse problem solution and more closely resembling an imaging turntable or inverse synthetic aperture radar. The heuristic derivation leads into the concept of the line integral and projections (the Radon Transform), followed by more general geometries where the plane wave approximation is invalid. We proceed next to study of the dependency of reconstruction on the space-frequency trajectory, combining the spatial aperture and waveform. Two and three dimensional apertures, monostatic and bistatic, fully and sparsely sampled and including partial apertures, with controlled waveforms (CW and pulsed, with and without modulation) define the filling of k-space and concomitant reconstruction performance. Theoretical developments in the first half of the thesis are applied to the specific example of bistatic tomographic imaging using High Definition Television (HDTV); the United States version of DVB-T. Modeling of the HDTV waveform using pseudonoise modulation to represent the hybrid 8VSB HDTV scheme and the move-stop-move approximation established the imaging potential, employing an idealized, isotropic 18 scatterer. As the move-stop-move approximation places a limitation on integration time (in cross correlation/pulse compression) due to transmitter/receiver motion, an exact solution for compensation of Doppler distortion is derived. The concept is tested with the assembly and flight test of a bistatic radar system employing software-defined radios (SDR). A three dimensional, bistatic collection aperture, exploiting an elevated commercial HDTV transmitter, is focused to demonstrate the principle. This work, to the best of our knowledge, represents a first in the formation of three dimensional images using bistatically-exploited television transmitters
- β¦