Waveform-Diverse Stretch Processing

Stretch processing with the use of a wideband LFM transmit waveform is a commonly used technique, and its popularity is in large part due to the large time-bandwidth product that provides fine range resolution capabilities for applications that require it. It allows pulse compression of echoes at a much lower sampling bandwidth without sacrificing any range resolution. Previously, this technique has been restrictive in terms of waveform diversity because the literature shows that the LFM is the only type of waveform that will result in a tone after stretch processing. However, there are also many examples in the literature that demonstrate an ability to compensate for distortions from an ideal LFM waveform structure caused by various hardware components in the transmitter and receiver. This idea of compensating for variations is borrowed here, and the use of nonlinear FM (NLFM) waveforms is proposed to facilitate more variety in wideband waveforms that are usable with stretch processing. A compensation transform that permits the use of these proposed NLFM waveforms replaces the final fast Fourier transform (FFT) stage of the stretch processing configuration, but the rest of the RF receive chain remains the same. This modification to the receive processing structure makes possible the use of waveform diversity for legacy radar systems that already employ stretch processing. Similarly, using the same concept of compensating for distortions to the LFM structure along with the notion that a Fourier transform is essentially the matched filter bank for an LFM waveform mixed with an LFM reference, a least-squares based mismatched filtering (MMF) scheme is proposed. This MMF could likewise be used to replace thefinal FFT stage, and can also facilitate the application of NLFM waveforms to legacy radar systems. The efficacy of these filtering approaches (compensation transform and least-squares based MMF) are demonstrated in simulation and experimentally using open-air measurements and are applied to different scenarios of NLFM waveform to assess the results and provide a means of comparison between the two techniques

Radar systems for the water resources mission, volume 2

The application of synthetic aperture radar (SAR) in monitoring and managing earth resources was examined. The function of spaceborne radar is to provide maps and map imagery to be used for earth resource and oceanographic applications. Spaceborne radar has the capability of mapping the entire United States regardless of inclement weather; however, the imagery must have a high degree of resolution to be meaningful. Attaining this resolution is possible with the SAR system. Imagery of the required quality must first meet mission parameters in the following areas: antenna patterns, azimuth and range ambiguities, coverage, and angle of incidence

Coordinating Complementary Waveforms for Sidelobe Suppression

We present a general method for constructing radar transmit pulse trains and receive filters for which the radar point-spread function in delay and Doppler, given by the cross-ambiguity function of the transmit pulse train and the pulse train used in the receive filter, is essentially free of range sidelobes inside a Doppler interval around the zero-Doppler axis. The transmit pulse train is constructed by coordinating the transmission of a pair of Golay complementary waveforms across time according to zeros and ones in a binary sequence P. The pulse train used to filter the received signal is constructed in a similar way, in terms of sequencing the Golay waveforms, but each waveform in the pulse train is weighted by an element from another sequence Q. We show that a spectrum jointly determined by P and Q sequences controls the size of the range sidelobes of the cross-ambiguity function and by properly choosing P and Q we can clear out the range sidelobes inside a Doppler interval around the zero- Doppler axis. The joint design of P and Q enables a tradeoff between the order of the spectral null for range sidelobe suppression and the signal-to-noise ratio at the receiver output. We establish this trade-off and derive a necessary and sufficient condition for the construction of P and Q sequences that produce a null of a desired order

Waveform Diversity and Range-Coupled Adaptive Radar Signal Processing

Waveform diversity may offer several benefits to radar systems though often at the cost of reduced sensitivity. Multi-dimensional processing schemes are known to offer many degrees of freedom, which can be exploited to suppress the ambiguity inherent to pulse compression, array processing, and Doppler frequency estimation. Spatial waveform diversity can be achieved by transmitting different but correlated waveforms from each element of an antenna array. A simple yet effective scheme is employed to transmit different waveforms in different spatial directions. A new reiterative minimum mean squared error approach entitled Space-Range Adaptive Processing, which adapts simultaneously in range and angle, is derived and shown in simulation to offer enhanced performance when spatial waveform diversity is employed relative to both conventional matched filtering and sequentially adapting in angle and then range. The same mathematical framework is utilized to develop Time-Range Adaptive Processing (TRAP) algorithm which is capable of simultaneously adapting in Doppler frequency and range. TRAP is useful when pulse-to-pulse changing of the center frequency or waveform coding is used to achieve enhanced range resolution or unambiguous ranging, respectively. The inherent computational complexity of the new multi-dimensional algorithms is addressed by segmenting the full-dimension cost functions, yielding a reduced-dimensional variants of each. Finally, a non-adaptive approach based on the multi-dimensional TRAP signal model is utilized to develop an efficient clutter cancellation technique capable of suppressing multiple range intervals of clutter when waveform diversity is applied to pulse-Doppler radar

Characterization and Validation of the GP-3 Experimental Radar System

The experimental GP-3 radar system was originally designed and built under contract for the Air Force Research Laboratory (AFRL). AFRL sought AFIT\u27s support in characterizing the as delivered\u27 performance of the GP-3. This research effort focused exclusively on software modifications and hardware validations related to the GP-3 post-processing mode. As modified, tested, and validated, the GP-3\u27s post-processing mode is now fully operational. The GP-3 is capable of transmitting and receiving bandlimited (3.5 MHz) waveforms at X-Band frequencies. System characterization tests included, noise performance and frequency response. System noise performance characterization permitted establishment of the receiver \u27noise floor\u27 and enabled determination of achievable SNRs (-22 dB to 44 dB for internal noise only). Frequency response characterization provided system coloration\u27 effects; an operational center frequency (4.25 MHz) and -3.0 dB bandwidth (4 MHz) were established. The GP-3\u27s operational post-processing capabilities were demonstrated for three systems: (1) a digital communication system, (2) a phase-coded, pulse compression radar, and (3) a radar employing nonlinear (range ambiguity) suppression (NLS). The GP-3 is now a viable research testbed - a highly capable system for adding an element of real-world credibility to any experimental, modeling, and simulation scenario

Development and characterization analysis of a radar polarimeter

The interaction of electromagnetic waves with natural earth surface was of interest for many years. A particular area of interest in controlled remote sensing experiments is the phenomena of depolarization. The development stages of the radar system are documented. Also included are the laboratory procedures which provides some information about the specifications of the system. The radar system developed is termed the Radar Polarimeter System. A better insight of the operation of the RPS in terms of the newly developed technique--synthetic aperture radar system is provided. System performance in tems of radar cross section, in terms of power, and in terms of signal to noise ratio are also provided. In summary, an overview of the RPS in terms of its operation and design as well as how it will perform in the field is provided

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