With the widespread application of unmanned aerial vehicles, higher requirements have been put forward for the detection of small targets moving at high speed. In this paper, we implement a millimeter wave Frequency Modulated Continuous Wave (FMCW) radar system with dual-receive channels to detect target motion parameters. In the radar system, a novel signal is designed to be composed of two FMCW signals whose instantaneous frequencies are symmetrical about carrier frequency, so as to get the estimation value of the targets' distance and radial velocity using doppler shift. Besides, signals of different periods are transmitted alternately to facilitate the removal of virtual targets. Furthermore, the height information of the target can be obtained through the interference of the signals received by the two channels. Based on the theory above, simulation results are provided to validate the effectiveness of the proposed approach and evaluate the performance of the radar system.

This paper presents a data gathering protocol for wireless sensor network applications that require high throughput, reliability, and low-power. Insofar as high throughput is concerned, TDMA is more suitable than CSMA. Efficient TDMA protocols require solid synchronization and more optimized time slot scheduling; reliable data collection calls for end-to-end packet retransmission. Such factors hinder the implementation of a comprehensive data collection protocol. In this paper, a heuristic TDMA scheduling algorithm is provided to achieve optimized time slot scheduling with multi-channel communication. The combination of TDMA and multi-channel communication affords to sustain high throughput and low-power. In addition, constructive interference based flooding is adopted to provide robust synchronization and efficient downward communication. We associate constructive interference based flooding with packet retransmission to implement collection reliability. The proposed protocol is implemented on Tmote Sky sensor node with Contiki operating system. Experimental results in a deployed network consisting of 29 sensor nodes show that it is able to provide throughput as high as 14.66KByte/s with 100% data collection.

TDMA is more suitable for high throughput data collection than CSMA. Yet, in wireless sensor network plain TDMA-based protocols require complex scheduling. In case of node failures, plain TDMA is hard to recover connection and achieve robust data collection due to the complex scheduling burden. Toward robust data collection, it is important to develop a collection protocol capable of topology adaptability. We have been developing a data gathering protocol named TKN-TWN. TKN-TWN exploits the advantages of TDMA and eases the scheduling burden by using two tokens to arbitrate transmission, providing high throughput via burst data transmission. Moreover, due to the simplified scheduling based on tokens, TKN-TWN is practical to provide adaptability for infrequent topology changes. We enhance the implementation of TKN-TWN over the previous work and carry out experiment on a deployed network in the office room to evaluate the throughput and topology adaptability as well. Experimental results in the network consisting of 32 TinyOS enabled sensor nodes show that TKN-TWN is robust to network changes caused by occasional node failures. Evaluation also shows that TKN-TWN is able to even provide throughput over 10 KByte/s.

To reduce the complexity of scheduling while exploiting the advantages of TDMA-based data collection, we propose TKN-TWN, a token-scheduled multi-channel data collection protocol. The TKN-TWN uses two tokens to arbitrate data-packet transmissions and associates the ownership of tokens with transmission slot assignment. For the reduction of scheduling burden, the TKN-TWN provides topology adaptability while maintaining high throughput in burst data transfer. In this paper, we present the system design of TKN-TWN with enhancement toward topology adaptability based on a previous work. We evaluate TKN-TWN on a local test bed using 31 TelosB sensor nodes. Evaluation results show that the TKN-TWN achieves throughput of 6.4 KByte/s with more than 99% delivery ratio even with occasional node failures.

We present a high throughput data gathering protocol for wireless sensor network. Different from existing works we elaborate a token-scheduled multi-channel TDMA protocol named TKN-TWN that provides better scalability and topology adaptability. TDMA is more suitable for high throughput data collection than CSMA. However, TDMA-based protocols require complex scheduling of the transmission time slot. The scheduling burden is a primary stumbling block of topology adaptability. To ease the scheduling burden while exploiting the advantages of TDMA, we propose to use two tokens arbitrate transmission and associate the ownership of tokens with transmission slot assignment toward throughput optimization. Due to the simplified scheduling based on tokens, TKN-TWN is able to provide scalability and topology adaptability. In addition, TKN-TWN allows burst transmission by leveraging the contention-free nature of TDMA, and sustains high throughput with burst data transmission when sensor nodes have similar traffic pattern. An extensive simulation study indicates that TKN-TWN achieves robust data delivery even in densely deployed large scale sensor networks. Experimental results on Tmote Sky show that TKN-TWN is able to provide throughput over 10 KByte/s, an improvement of about 23% over a prior work.