The main objective of this work is to improve the performance of spread spectrum techniques in different applications. The applications that will be considered in this thesis are. 1. Automotive Radar. 2. Indoor Positioning Systems. 3. Ultrasonic and Microwave Imaging. The problems associated with the above mentioned systems are: 1. Noise Effect. 2. Accuracy of the System. 3. Resolution of the System. For the automotive radar an e±cient, accurate and easy to implement system for a sideways-looking radar signal processing is presented. The system is designed to work with a spread spectrum signal. A new method for implementing the shifting of the PN code is proposed. It is applied for calculating the correlation function which is used to measure the target range. The proposed method results in a higher accuracy without increasing the chip rate of the PN code (which necessitates increasing the bandwidth). Also the proposed method has the facility of variable accuracy without increasing the complexity of the system. Results on measurement of the distance to and the velocity of a moving vehicle are presented. In the automotive radar it is very important to reduce the required transmitted power in order to reduce the interference due to the existence of multi radar systems on the high ways and also to save the battery of the car. Reducing the transmitted power will lead to the problem of weak signal detection. Weak signal detection and localization are therefore basic and important problems in radar systems. Radar performance can be improved by increasing the receiver output signal-to-noise ratio (SNR) without the need for increasing the transmitted power. This can be achieved by cleaning up the received signal from the noise (denoising). An algorithm is described for extracting and localizing an RF radar pulse from a noisy background. The algorithm combines two powerful tools: The wavelet packet analysis and the higher-order-statistics (HOS). The use of the proposed technique makes detection and localization of RF radar pulses possible in very low SNR conditions, which leads to a reduction of the required microwave power or alternatively extending the detection range of radar systems. The second application to be considered is the positioning. One of the greet advantages of spread spectrum techniques is the multi user access, which encourage the people working in the fieled of local positioning systems to use it. Many mobile applications can be greatly enhanced when provided with the locations of people and devices. Indoor ultrasonic positioning systems provide fine-grained position data for such applications. An ultrasonic tagging system developed for monitoring the location of a moving target is considered in this work. Use of spread spectrum in ultrasonic location systems allows the system to work at a noisy environment. At the same time it solves the problem of signal collisions when more than one transmitter transmit at the same time. Test results demonstrate that the system is able to locate the position of a moving target with high accuracy. Most of the existing ultrasonic transducers used in local positioning systems have a limited bandwidth, which leads to a poor resolution in locating the position of a target duo to multi-path reflections from the surroundings. Different super resolution techniques such as Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) and Multiple Signal Classification (MUSIC) have been used for spectral estimation applications. The proposed system in this thesis solves the problem of limitation in ultrasonic transducers bandwidth by applying the RMUSIC super resolution technique to estimate the time of arrival of ultrasonic signal. As a third application imaging is considered. Resolution and noise effects are primary criteria. Conventionally, high bandwidth for resolution was achieved with a short pulse, which results in a trade-off between resolution and noise effect. Peak acoustic power limits the SNR of real-time ultrasound imaging. The SNR can be signifecantly increased using coded excitation. A coded system transmits a broadband pulse with a finite time-bandwidth product. The received signal must be decoded to produce an imaging pulse with improved SNR resulting from higher average power in the excitation. However, decoding can produce significant range side lobes greatly reducing image quality or image resolution. All practical coding designs, therefore, represent a trade-off between SNR gain and range side lobes. The root multiple signal classification (RMUSIC) algorithm is a known technique in multi-path detection in communication. In this thesis we propose using the RMUSIC algorithm to overcome the problem of range side lobes. Results indicate that the RMUSIC algorithm is able to perfectly reconstruct the decoded pulse without any range side lobes effect. This will leads to a greet improvement in SNR coded excitation techniques without reduction in the image quality or image resolution. Beside the ultrasonic imaging the problem of bandwidth limitation in microwave imaging is considered as well. The thesis proposes a technique for reconstructing one-dimensional stratified permittivity profiles. The proposed technique is based on the inversion of the measured frequency-domain reflection coefficient of the profile into a virtual time domain. The inversion of the reflection coe±cient is based on the super resolution technique RMUSIC. The advantage of using this technique is its ability to remove the side lobe effect caused by the limited measurement bandwidth. Measurements using different materials have been carried out to validate the quality of the proposed technique.
spread spectrum, Automotive Radar, Indoor Positioning Systems, Ultrasonic and Microwave Imaging super resolution technique and wavelet transform