Compressive Sensing (CS) theory is a newly developed theory which combines the signal sampling and compression based on the sparsity characteristics of the signal. Applying CS theory in radar signal processing may lead to a reduction in sampling rate, complexity, power consumption, and cost. On the other hand, performance is a critical point to be considered. In the present paper, an important question of the worthy of applying CS in the signal processing of Linear Frequency Modulated Continuous Wave (LFMCW) radar is considered. Two approaches of CS are considered; Nyquist rate based approach, and pseudo random based approach. The detection performance of LFMCW radar signal processor using CS based approaches is compared to the traditional one which is based on Fast Fourier Transform (FFT) through Receiver Operating Characteristics (ROC) curves. Comparative analysis between CS approaches and the traditional one regarding the performance and complexity is presented.

Application of Compressive Sensing (CS) in Linear Frequency Modulation Continuous Wave ( LFMCW) radar had been investigated and proved by the authors in [8]. An approach, namely architecture 1, had been evaluated by the authors in [11] which dependent mainly on applying CS in range direction. But there is a limitation on the number of the detected targets in range. So, in the present paper, a new approach for applying CS in LFMCW radar signal processing, namely architecture 2, is introduced depends on apply CS in azimuth direction (range sweeps). The reduction in range sweeps is performed using a Pseudo Random (PN) sequence in Azimuth according to the required reduction ratio in range sweeps. The information of the received radar signal (target range and speed) are reconstructed by the use of Complex Approximate Message Passing (CAMP) reconstruction algorithm. Performance of the proposed LFMCW radar signal processors based on CS (architecture2) is evaluated and compared to that of both the traditional one based on Fast Fourier Transform (FFT)) and architecture 1 from points of view of detection performance throughReceiver Operating Characteristics (ROC) curves, resolution performance and hardware complexity. The proposed approach (architecture 2) is designed and implemented using Field Programmable Gate Array (FPGA).

Application of Compressive Sensing (CS) in Linear Frequency Modulation Continuous Wave (LFMCW) radar had been investigated and proved by the authors in [8]. In this paper, a new approach for applying CS in LFMCW radar signal processing is introduced. The proposed approach depends on apply CS in range processing direction by acquiring the base band radar signal with a sampling rate, according to a Pseudo Random (PN) sequence, less than that of the well known Nyquist rate. The information of the received radar signal (target range and speed) are reconstructed by the use of Complex Approximate Message Passing (CAMP) reconstruction algorithm. The superiority of the proposed LFMCW radar signal processor (Based on CS) compared to that of the traditional one (based on Fast Fourier Transform (FFT)) from points of view of detection performance through Receiver Operating Characteristics (ROC) curves, resolution performance and hardware complexity is validated.

The radar warning receiver (RWR) is the heart of the self protection system of modern aircraft. The most important receiver structures that can be used as RWR are the crystal video receiver (CVR) and the instantaneous frequency measurement (IFM) receiver. This paper presents a complete design and implementation of the microwave part of the CVR. This CVR is designed to cover a frequency ranging from 1.5 up to 4 GHz. The CVR is implemented using the recently developed microstrip technology. The designed receiver was successfully tested and the results in terms of the output voltage and the voltage standing wave ratio (VSWR) were very good. This paper presents also a complete design and implementation of the critical components of the IFM receiver. These components are the phase correlator, the power dividers, the delay line, the square law detectors preceded by broadband matching circuits, and the low pass filter. They are implemented using the microstrip technology. The input to the correlator is the threatening radar signal and the output comprises four video signals that can be processed to obtain the signal frequency instantaneously. A new design procedure is proposed to overcome the problems, usually encountered when trying to design and implement phase correlators. The designed correlator was successfully tested and found to operate adequately in the whole S-band.