In this thesis signal processing techniques for the Ultra-wide-band impulse radar (UWB-IR) radar are dis-cussed. To context wherein these algorithms are used is in a car, with the aim of detecting a child left behind in the car. This thesis also touches on algorithms to obtain vital information of the child inside the car. To this end a mathematical model for chest movement causes by breathing and heartbeat is made and explained. From this mathematical description data is derived in the form of a range-time matrix in MATLAB. The functioning of the algorithms is then showcased using this data. Regarding the algorithms. This thesis discusses 3 potential filters that can be implemented in the signal processing scheme. These are the adaptive, average, and exponential filters. Their hardware implementation is spoken of as well as their implementation in MATLAB. The algorithm for detecting of humans are also covered with emphasis on the threshold used for this. Finally the last step in the signal processing scheme, the measuring of breathing- and heart-beat frequency ,is worked out in the form of four additional algorithms which include: Fast Fourier transform, Hilbert Huang transform, The centroid algorithm, Cumulative summation. This thesis then finally tests these four algorithms in form of a complete signal processing algorithm using real world experimental data. Then by considering all aspects of the scheme, from hardware implementation, efficiency, functionality and precision, the algorithm that works best for our goal of detecting a child in a car is chosen.