336 research outputs found
In pursuit of high resolution radar using pursuit algorithms
Radar receivers typically employ matched filters designed to maximize signal to noise ratio (SNR) in a single target environment. In a multi-target environment, however, matched filter estimates of target environment often consist of spurious targets because of radar signal sidelobes. As a result, matched filters are not suitable for use in high resolution radars operating in multi-target environments. Assuming a point target model, we show that the radar problem can be formulated as a linear under-determined system with a sparse solution. This suggests that radar can be considered as a sparse signal recovery problem. However, it is shown that the sensing matrix obtained using common radar signals does not usually satisfy the mutual coherence condition. This implies that using recovery techniques available in compressed sensing literature may not result in the optimal solution. In this thesis, we focus on the greedy algorithm approach to solve the problem and show that it naturally yields a quantitative measure for radar resolution. In addition, we show that the limitations of the greedy algorithms can be attributed to the close relation between greedy matching pursuit algorithms and the matched filter. This suggests that improvements to the resolution capability of the greedy pursuit algorithms can be made by using a mismatched signal dictionary. In some cases, unlike the mismatched filter, the proposed mismatched pursuit algorithm is shown to offer improved resolution and stability without any noticeable difference in detection performance. Further improvements in resolution are proposed by using greedy algorithms in a radar system using multiple transmit waveforms. It is shown that while using the greedy algorithms together with linear channel combining can yield significant resolution improvement, a greedy approach using nonlinear channel combining also shows some promise. Finally, a forward-backward greedy algorithm is proposed for target environments comprising of point targets as well as extended targets
Good Code Sets from Complementary Pairs via Discrete Frequency Chips
It is shown that replacing the sinusoidal chip in Golay complementary code
pairs by special classes of waveforms that satisfy two conditions,
symmetry/anti-symmetry and quazi-orthogonality in the convolution sense,
renders the complementary codes immune to frequency selective fading and also
allows for concatenating them in time using one frequency band/channel. This
results in a zero-sidelobe region around the mainlobe and an adjacent region of
small cross-correlation sidelobes. The symmetry/anti-symmetry property results
in the zero-sidelobe region on either side of the mainlobe, while
quasi-orthogonality of the two chips keeps the adjacent region of
cross-correlations small. Such codes are constructed using discrete
frequency-coding waveforms (DFCW) based on linear frequency modulation (LFM)
and piecewise LFM (PLFM) waveforms as chips for the complementary code pair, as
they satisfy both the symmetry/anti-symmetry and quasi-orthogonality
conditions. It is also shown that changing the slopes/chirp rates of the DFCW
waveforms (based on LFM and PLFM waveforms) used as chips with the same
complementary code pair results in good code sets with a zero-sidelobe region.
It is also shown that a second good code set with a zero-sidelobe region could
be constructed from the mates of the complementary code pair, while using the
same DFCW waveforms as their chips. The cross-correlation between the two sets
is shown to contain a zero-sidelobe region and an adjacent region of small
cross-correlation sidelobes. Thus, the two sets are quasi-orthogonal and could
be combined to form a good code set with twice the number of codes without
affecting their cross-correlation properties. Or a better good code set with
the same number codes could be constructed by choosing the best candidates form
the two sets. Such code sets find utility in multiple input-multiple output
(MIMO) radar applications
A novel approach to robust radar detection of range-spread targets
This paper proposes a novel approach to robust radar detection of
range-spread targets embedded in Gaussian noise with unknown covariance matrix.
The idea is to model the useful target echo in each range cell as the sum of a
coherent signal plus a random component that makes the signal-plus-noise
hypothesis more plausible in presence of mismatches. Moreover, an unknown power
of the random components, to be estimated from the observables, is inserted to
optimize the performance when the mismatch is absent. The generalized
likelihood ratio test (GLRT) for the problem at hand is considered. In
addition, a new parametric detector that encompasses the GLRT as a special case
is also introduced and assessed. The performance assessment shows the
effectiveness of the idea also in comparison to natural competitors.Comment: 28 pages, 8 figure
Nearly orthogonal, doppler tolerant waveforms and signal processing for multi-mode radar applications
In this research, we investigate the design and analysis of nearly orthogonal, Doppler tolerant waveforms for diversity waveform radar applications. We then present a signal processing framework for joint synthetic aperture radar (SAR) and ground moving target indication (GMTI) processing that is built upon our proposed waveforms. ^ To design nearly orthogonal and Doppler tolerant waveforms, we applied direct sequence spread spectrum (DSSS) coding techniques to linear frequency modulated (LFM) signals. The resulting transmitted waveforms are rendered orthogonal using a unique spread spectrum code. At the receiver, the echo signal can be decoded using its spreading code. In this manner, transmit orthogonal waveforms can be matched filtered only with the intended receive signals. ^ Our proposed waveforms enable efficient SAR and GMTI processing concurrently without reconfiguring a radar system. Usually, SAR processing requires transmit waveforms with a low pulse repetition frequency (PRF) rate to reduce range ambigu- ity; on the other hand, GMTI processing requires a high PRF rate to avoid Doppler aliasing and ambiguity. These competing requirements can be tackled by employing some waveforms (with low PRF) for the SAR mission and other waveforms (with high PRF) for the GMTI mission. Since the proposed waveforms allow separation of individual waveforms at the receiver, we can accomplish both SAR and GMTI processing jointl
- …